Biology subjects

Ghuman, A. S.

Publications and source records attributed to Ghuman, A. S..

11 recordsLinked to original sources

bioRxiv2024

Is there a ubiquitous spectrolaminar motif of local field potential power across primate neocortex?

Mendoza-Halliday, Major et al.1 (referred to as "Mendoza-Halliday et al." for brevity), advocate for a local field potential (LFP)-based approach to functional identification of cortical layers during "laminar" (simultaneous recordings from all cortical layers) multielectrode recordings in nonhuman primates (NHPs). They describe a "ubiquitous spectrolaminar motif" in the primate neocortex: 1) 75-150 Hz power peaks in the supragranular layers, 2) 10-19 Hz power peaks in the infragranular layers and 3) the crossing point of their laminar power gradients identifies Layer 4 (L4). Identification of L4 is critical in general, but especially for Mendoza-Halliday et al. as the "motif" discovery is couched within a framework whose central hypothesis is that gamma activity originates in the supragranular layers and reflects feedforward activity, while alpha-beta activity originates in the infragranular layers and reflects feedback activity. In an impressive scientific effort, Mendoza-Halliday et al. analyzed laminar data from 14 cortical areas in 2 prior macaque studies and compared them to marmoset, mouse, and human data to further bolster the canonical nature of the motif. Identification of such canonical principles of brain operation is clearly a topic of broad scientific interest. Similarly, a reliable online method for L4 identification would be of broad scientific value for the rapidly increasing use of laminar recordings using numerous evolving technologies. Despite Mendoza-Halliday et al.s papers strengths, and its potential for scientific impact, a series of concerns that are fundamental to the analysis and interpretation of laminar activity profile data in general, and local field potential (LFP) signals in particular, led us to question its conclusions. Here, we address four key questions: Q1) Is the spectrolaminar motif ubiquitous, i.e. "found everywhere" or "universal"? Q2) Do features of the motif reliably identify Layer (L) 4? Q3) Are Mendoza-Halliday et al.s newly introduced methods (FLIP and vFLIP) reliable? And Q4) Are the proposed biophysical mechanisms underlying the motif well justified? We used new sets of data comprised of stimulus-evoked laminar response profiles from primary and higher-order auditory cortices (A1 and belt cortex), and primary visual cortex (V1) to test these questions. The rationale for using these areas as a test bed for new methods is that, in contrast to higher-order cortical areas, their laminar anatomy and physiology have already been extensively characterized by prior studies, and there is general agreement across laboratories on key matters like L4 identification. In short, we find that Mendoza-Halliday et al.s findings do not generalize well to these cortical areas. Specifically, regarding Q1: Though we can find a spectrolaminar gradient that is qualitatively consistent with Mendoza-Halliday et al., it is quantifiable in only 61-64% of our recordings, indicating that the motif is common but by no means universal (see "Evaluation of the FLIP method [...]" and "Evaluation of vFLIP [...]"). Regarding Q2: The motifs high/low frequency gradient cross point identified L4 in only 29-33% of our recordings. Regarding Q3: FLIP and vFLIP exhibit marked variability across studies, across brain areas, and spuriously detect cortical layer inversions (see "FLIPs fitting process [...]" and "Evaluation of vFLIP [...]"). Regarding Q4: the biophysical modeling findings cited to support Mendoza-Hallidays conclusions (see "Going forward - in silico [...]") do not reproduce the LFP data trends. While our findings are in many respects at odds with those of Mendoza-Halliday et al., the paper already has, and will continue to spark debate and further experimentation. Hopefully this countervailing presentation will lead to robust collegial efforts to define optimal strategies for applying laminar recording methods in future studies.

neuroscience↗

bioRxiv2024

A hierarchy of processing complexity and timescales for natural sounds in human auditory cortex

Efficient behavior is supported by humans ability to rapidly recognize acoustically distinct sounds as members of a common category. Within auditory cortex, there are critical unanswered questions regarding the organization and dynamics of sound categorization. Here, we performed intracerebral recordings in the context of epilepsy surgery as 20 patient-participants listened to natural sounds. We built encoding models to predict neural responses using features of these sounds extracted from different layers within a sound-categorization deep neural network (DNN). This approach yielded highly accurate models of neural responses throughout auditory cortex. The complexity of a cortical sites representation (measured by the depth of the DNN layer that produced the best model) was closely related to its anatomical location, with shallow, middle, and deep layers of the DNN associated with core (primary auditory cortex), lateral belt, and parabelt regions, respectively. Smoothly varying gradients of representational complexity also existed within these regions, with complexity increasing along a posteromedial-to-anterolateral direction in core and lateral belt, and along posterior-to-anterior and dorsal-to-ventral dimensions in parabelt. When we estimated the time window over which each recording site integrates information, we found shorter integration windows in core relative to lateral belt and parabelt. Lastly, we found a relationship between the length of the integration window and the complexity of information processing within core (but not lateral belt or parabelt). These findings suggest hierarchies of timescales and processing complexity, and their interrelationship, represent a functional organizational principle of the auditory stream that underlies our perception of complex, abstract auditory information.

neuroscience↗

bioRxiv2022

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↗

bioRxiv2021

A Multimodal Approach to Investigate the Neural Mechanisms of Real World Social Vision

Eye tracking and other behavioral measurements collected from patient-participants in their hospital rooms afford a unique opportunity to study immersive natural behavior for basic and clinical translational research. We describe an immersive social and behavioral paradigm implemented in patients undergoing evaluation for surgical treatment of epilepsy, with electrodes implanted in the brain to determine the source of their seizures. Our studies entail collecting eye tracking with other behavioral and psychophysiological measurements from patient-participants during unscripted behavior, including social interactions with clinical staff, friends and family, in the hospital room. This approach affords a unique opportunity to study the neurobiology of natural social behavior, though it requires carefully addressing distinct logistical, technical, and ethical challenges. Collecting neurophysiological data synchronized to behavioral and psychophysiological measures helps us to study the relationship between behavior and physiology. Combining across these rich data sources while participants eat, read, converse with friends and family, etc., enables clinical-translational research aimed at understanding the participants disorders and clinician-patient interactions, as well as basic research into natural, real-world behavior. We discuss data acquisition, quality control, annotation, and analysis pipelines that are required for our studies. We also discuss the clinical, logistical, and ethical and privacy considerations critical to working in the hospital setting.

neuroscience↗

bioRxiv2021

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↗

bioRxiv2020

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↗

bioRxiv2020

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↗

bioRxiv2019

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↗

bioRxiv2019

Endogenous activity modulates stimulus and circuit-specific neural tuning and perception

Perception reflects not only input from the sensory periphery, but also the endogenous neural state when sensory inputs enter the brain. Whether endogenous neural states influence perception only through global mechanisms, such as arousal, or can also perception in a neural circuit and stimulus specific manner remains largely unknown. Intracranial recordings from 30 pre-surgical epilepsy patients showed that endogenous activity independently modulated the strength of trial-by-trial neural tuning of different visual category-selective neural circuits. Furthermore, the same aspect of the endogenous activity that influenced tuning in a particular neural circuit also correlated with reaction time only for trials with the category of image that circuit was selective for. These results suggest that endogenous activity may influence neural tuning and perception through circuit-specific predictive coding processes.

neuroscience↗

bioRxiv2018

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↗

bioRxiv2018

Posterior and Mid-Fusiform Contribute to Distinct Stages of Facial Expression Processing

Though the fusiform is well-established as a key node in the face perception network, its role in facial expression processing remains unclear, due to competing models and discrepant findings. To help resolve this debate, we recorded from 17 subjects with intracranial electrodes implanted in face sensitive patches of the fusiform. Multivariate classification analysis showed that facial expression information is represented in fusiform activity, in the same regions that represent identity, though with a smaller effect size. Examination of the spatiotemporal dynamics revealed a functional distinction between posterior and mid-fusiform expression coding, with posterior fusiform showing an early peak of facial expression sensitivity at around 180 ms after subjects viewed a face and mid-fusiform showing a later and extended peak between 230 - 460 ms. These results support the hypothesis that the fusiform plays a role in facial expression perception and highlight a qualitative functional distinction between processing in posterior and mid-fusiform, with each contributing to temporally segregated stages of expression perception.

neuroscience↗