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Boring, M. J.

Publications and source records attributed to Boring, M. J..

7 recordsLinked to original sources

Interacting cortical gradients of neural timescales and functional connectivity and their relationship to perceptual behavior

Cognitive acts take place over a large range of temporal scales. Numerous corresponding gradients in neurodynamic timescales and long-range cortical interactions are believed to provide organizational constraints to the brain and influence neural populations roles in cognition. However, it is unclear if gradients in various types of neural timescales and functional connectivity arise from related or distinct neurophysiological processes and if they influence behavior. Here, intracranial recordings from 4,090 electrode contacts in 35 individuals were used to systematically map gradients of multiple aspects of neurodynamics, neural timescales, and functional connectivity, and assess their interactions along category-selective ventral temporal cortex. Opposing functional connectivity gradients, with decreasing connectivity to visually responsive regions and increasing connectivity to regions that were not visually responsive, were observed along the ventral visual hierarchy. Endogenous neural timescales were correlated with functional connectivity to visually responsive regions after removing the effects of shared anatomical gradients, suggesting that these properties influence one another. Different stimulus evoked and endogenous timescales exhibited gradients with longer dynamics along the ventral visual hierarchy, but none of these timescales were significantly correlated with one another. This suggests that local neural timescales depend on neural and cognitive context and different timescales may arise through distinct neurophysiological processes. Furthermore, activity from neural populations with faster endogenous timescales and stronger functional connectivity to visually responsive regions was more predictive of perceptual behavior during a visual repeat detection task. These results reveal interrelationships and key distinctions among neural timescale and functional connectivity gradients that together can influence behavior.

neuroscience↗

Deep Brain Stimulation for Parkinson's Disease Induces Spontaneous Cortical Hypersynchrony In Extended Motor and Cognitive Networks

The mechanism of action of deep brain stimulation (DBS) for Parkinsons disease remains unclear. Studies have shown that DBS decreases pathological beta hypersynchrony between the basal ganglia and motor cortex. However, little is known about DBSs effects on long range corticocortical synchronization. Here, we use machine learning combined with spectral graph theory to compare resting-state cortical connectivity between the off and on-stimulation states and compare these differences to healthy controls. We found that turning DBS on increased high beta and gamma band coherence in a cortical circuit spanning the motor, occipitoparietal, middle temporal, and prefrontal cortices. We found no significant difference between DBS-off and controls in this network with multivariate pattern classification showing that the brain connectivity pattern in control subjects is more like those during DBS-off than DBS-on. These results show that therapeutic DBS increases spontaneous high beta-gamma synchrony in a network that couples motor areas to broader cognitive systems.

neuroscience↗

Multiple adjoining word and face selective regions in ventral temporal cortex exhibit distinct dynamics

The map of category-selectivity in human ventral temporal cortex (VTC) provides organizational constraints to models of object recognition. One important principle is lateral-medial response biases to stimuli that are typically viewed in the center or periphery of the visual field. However, little is known about the relative temporal dynamics and location of regions that respond preferentially to stimulus classes that are centrally viewed, like the face- and word-processing networks. Here, word- and face-selective regions within VTC were mapped using intracranial recordings from 36 patients. Partially overlapping, but also anatomically dissociable patches of face- and word-selectivity were found in VTC. In addition to canonical word-selective regions along the left posterior occipitotemporal sulcus, selectivity was also located medial and anterior to face-selective regions on the fusiform gyrus at the group level and within individual subjects. These regions were replicated using 7 Tesla fMRI in healthy subjects. Left hemisphere word-selective regions preceded right hemisphere responses by 125 ms, potentially reflecting the left hemisphere bias for language; with no hemispheric difference in face-selective response latency. Word-selective regions along the posterior fusiform responded first, then spread medially and laterally, then anteriorally. Face-selective responses were first seen in posterior fusiform regions bilaterally, then proceeded anteriorally from there. For both words and faces, the relative delay between regions was longer than would be predicted by purely feedforward models of visual processing. The distinct time-courses of responses across these regions, and between hemispheres, suggest a complex and dynamic functional circuit supports face and word perception. Significance StatementRepresentations of visual objects in the human brain have been shown to be organized by several principles, including whether those objects tend to be viewed centrally or peripherally in the visual field. However, it remains unclear how regions that process objects that are viewed centrally, like words and faces, are organized relative to one another. Here, invasive and non-invasive neuroimaging suggests there is a mosaic of regions in ventral temporal cortex that respond selectively to either words or faces. These regions display differences in the strength and timing of their responses, both within and between brain hemispheres, suggesting they play different roles in perception. These results illuminate extended, bilateral, and dynamic brain pathways that support face perception and reading.

neuroscience↗

Dynamic Domain Specificity In Human Ventral Temporal Cortex

An enduring neuroscientific debate concerns the extent to which neural representation is restricted to neural populations specialized for particular domains of perceptual input, or distributed outside of highly selective populations as well. A critical level for this debate is the neural representation of the identity of individual images, such as individual-level face or written word recognition. Here, intracranial recordings throughout ventral temporal cortex across 17 human subjects were used to assess the spatiotemporal dynamics of individual word and face processing within and outside regions strongly selective for these categories of visual information. Individual faces and words were first discriminable primarily only in strongly selective areas, beginning at about 150 milliseconds after word or face onset, and then discriminable both within and outside strongly selective areas approximately 170 milliseconds later. Regions of ventral temporal cortex that were and were not strongly selective both contributed non-redundant information to the discrimination of individual images. These results can reconcile previous results endorsing disparate poles of the domain specificity debate by highlighting the temporally segregated contributions of different functionally defined cortical areas to individual level representations. This work supports a dynamic model of neural representation characterized by successive domain-specific and distributed processing stages.

neuroscience↗

Shrinkage Classification for Overlapping Time Series: An interpretable method for mapping stimulus-differentiated evoked response

Multivariate time series from neural electrophysiological recordings are a rich source of information about neural processing systems and require appropriate methods for proper analysis. Current methods for mapping brain function in these data using neural decoding aggregate information across space and time in limited ways, rarely incorporating spatial dependence across recording locations. We propose Shrinkage Classification for Overlapping Time Series (SCOTS), a neural decoding method that maps brain function, while accounting for spatio-temporal dependence, through interpretable dimensionality reduction and classification of multivariate neural time series. SCOTS has two components: first, overlapping clustering from sparse semi-nonnegative matrix factorization gives a data-driven aggregation of neural information across space; second, wavelet-transformed nearest shrunken centroids with sparse group lasso performs multi-class classification with selection of informative clusters and time intervals. We demonstrate use of SCOTS by applying it to human intracranial electrophysiological and MEG data collected while participants viewed visual stimuli from a range of categories. The method reveals the dynamic activation of brain regions with sensitivity to different object categories, giving insight into spatio-temporal contributions of these neural processing systems.

neuroscience↗

The left midfusiform gyrus interacts with early visual cortex and the anterior temporal lobe to support word individuation.

The left mid-ventral temporal cortex (lmVTC) plays a dynamic role in reading. In this study we investigated the neural interactions that influence lmVTC dynamics and the lexical information these interactions are dependent on. We monitored activity with either intracranial electroencephalography or magnetoencephalography while participants viewed real words, pseudowords, consonant strings, and false fonts. A coarse level representation in early lmVTC activity allowed for decoding of visually dissimilar real words, pseudowords, and false fonts. Functional interactions between anterior ventral temporal regions, possibly containing stored knowledge about words, and low-order visual regions occurred after this initial stage of processing and was followed by the individuation of orthographically similar real words in lmVTC, but not similar pseudowords, letter strings, or false fonts. These results suggest that the individuation of real word representations in lmVTC is catalyzed by stored knowledge about word forms that emerges from network-level interactions with anterior regions of the temporal lobe.

neuroscience↗

Very high density EEG elucidates spatiotemporal aspects of early visual processing

Standard human EEG systems based on spatial Nyquist estimates suggest that 20-30 mm electrode spacing suffices to capture neural signals on the scalp, but recent studies posit that increasing sensor density can provide higher resolution neural information. Here, we compared \"super-Nyquist\" density EEG (\"SND\") with Nyquist density (\"ND\") arrays for assessing the spatiotemporal aspects of early visual processing. EEG was measured from 128 electrodes arranged over occipitotemporal brain regions (14 mm spacing) while participants viewed flickering checkerboard stimuli. Analyses compared SND with ND-equivalent subsets of the same electrodes. Frequency-tagged stimuli were classified more accurately with SND than ND arrays in both the time and the frequency domains. Representational similarity analysis revealed that a computational model of V1 correlated more highly with the SND than the ND array. Overall, SND EEG captured more neural information from visual cortex, arguing for increased development of this approach in basic and translational neuroscience.\n\nAbbreviations

neuroscience↗