Biology subjects

Megevand, P.

Publications and source records attributed to Megevand, P..

9 recordsLinked to original sources

bioRxiv2026

Cortico-hippocampal dynamics of hierarchical syntactic planning in natural speech production

The human brain must rapidly construct hierarchical structures to organize complex sequential behavior, yet the neural dynamics supporting this process during natural behavior remain poorly understood. Spoken language provides a powerful model system for investigating this computation, requiring rapid transformation of conceptual intent into structured sequential output. Using rare intracranial stereo-electroencephalography (SEEG) recordings from patients producing extended spontaneous speech, we examined how syntactic planning unfolds over time using measures of constituency, dependency structure, and probabilistic syntactic categories. We identified a hierarchical planning architecture in which global sentence structure and core syntactic categories (nouns and verbs) were specified before more local planning operations. Neural representations of these categories emerged up to 1 s before articulation and persisted throughout the planning period, whereas optional modifiers, including adjectives and adverbs, were recruited only closer to speech onset. These observations support a model of hierarchical incremental planning in which abstract sentence structure precedes the incremental specification of individual sentence elements. While core syntactic categories engaged a broader fronto-temporo-parietal network than other word classes, syntactic-depth-related activity emerged in parallel across cortical regions and the hippocampus, suggesting that hippocampal relational representations contribute to sentence structure building. Together, these findings support a cortico-hippocampal model of speech production in which hierarchical sentence structure and core syntactic categories are planned before secondary syntactic elements are incrementally incorporated into the evolving sentence plan. These results provide a neural account of how abstract linguistic structure is transformed into fluent speech.

neuroscience↗

bioRxiv2025

Multiple task-demands flexibly optimize neural geometry in human ventral temporal cortex

A hallmark of human intelligence is the ability to perform multiple tasks immediately upon instruction. Yet, the neural processes that implement such flexibility remain unclear. Using intracranial electrophysiology in epilepsy patients, we examined how representational geometries evolve as participants switched among three tasks - individuation, categorization, and conceptualization - on a trial-by-trial basis. Although tasks differed in the required representational geometries, neural representations across cortex were not immediately optimized following task cues. Instead, task-tailored geometries emerged gradually over successive stimulus repetitions within a trial. Ventral temporal cortex was the only region to exhibit task-specific adjustments for all three tasks, dynamically transforming within- and between-category distances in line with task demands. Importantly, these gradual representational changes were behaviorally relevant, predicting trial-level performance. Our results show that behavioral flexibility is supported by incremental, task-dependent refinement of representational geometry already within sensory cortex - far earlier in the processing hierarchy than previously thought.

neuroscience↗

bioRxiv2021

Information flows from hippocampus to cortex during replay of verbal working memory items.

The maintenance of items in working memory relies on a widespread network of cortical areas and hippocampus where synchronization between electrophysiological recordings reflects functional coupling. We investigated the direction of information flow between auditory cortex and hippocampus while participants heard and then mentally replayed strings of letters in working memory by activating their phonological loop. We recorded LFP from the hippocampus, reconstructed beamforming sources of scalp EEG, and - additionally in 3 participants - recorded from subdural cortical electrodes. When analyzing Granger causality, the information flow was from auditory cortex to hippocampus with a peak in the 4-8 Hz range while participants heard the letters. This flow was subsequently reversed during maintenance while participants maintained the letters in memory. The functional interaction between hippocampus and the cortex and the reversal of information flow provide a physiological basis for the encoding of memory items and their active replay during maintenance.

neuroscience↗

bioRxiv2021

Imagined speech can be decoded from low- and cross-frequency features in perceptual space

Reconstructing intended speech from neural activity using brain-computer interfaces (BCIs) holds great promises for people with severe speech production deficits. While decoding overt speech has progressed, decoding imagined speech have met limited success, mainly because the associated neural signals are weak and variable hence difficult to decode by learning algorithms. Using three electrocorticography datasets totalizing 1444 electrodes from 13 patients who performed overt and imagined speech production tasks, and based on recent theories of speech neural processing, we extracted consistent and specific neural features usable for future BCIs, and assessed their performance to discriminate speech items in articulatory, phonetic, vocalic, and semantic representation spaces. While high-frequency activity provided the best signal for overt speech, both low- and higher-frequency power and local cross-frequency contributed to successful imagined speech decoding, in particular in phonetic and vocalic, i.e. perceptual, spaces. These findings demonstrate that low-frequency power and cross-frequency dynamics contain key information for imagined speech decoding, and that exploring perceptual spaces offers a promising avenue for future imagined speech BCIs.

neuroscience↗

bioRxiv2020

Functional synchronization between hippocampal sEEG, parietal ECoG and scalp EEG during a verbal working memory task.

BackgroundThe maintenance of items in working memory (WM) relies on a widespread network of brain areas where synchronization between electrophysiological recordings may reflect functional coupling. While the coupling from hippocampus to scalp EEG is well established, we provide here direct cortical recordings for a fine-grained analysis. MethodsA patient performed a WM task where a string of letters was presented all at once, thus separating the encoding period from the maintenance period. We recorded sEEG from the hippocampus, temporo-parietal ECoG from a 64-contact grid electrode, and scalp EEG. ResultsPower spectral density (PSD) showed a clear task dependence: PSD in the posterior parietal lobe (10 Hz) and in the hippocampus (20 Hz) peaked towards the end of the maintenance period. Inter-area synchronization was characterized by the phase locking value (PLV). WM maintenance enhanced PLV between hippocampal sEEG and scalp EEG specifically in the theta range [6 7] Hz. PLV from hippocampus to parietal cortex increased during maintenance in the [9 10] Hz alpha and the 20 Hz range. When analyzing the information flow to and from auditory cortex by Granger causality, the flow was from auditory cortex to hippocampus with a peak in the [8 18] Hz range while letters were presented, and this flow was subsequently reversed during maintenance, while letters were maintained in memory. ConclusionsThe increased functional interaction between hippocampus and cortex through synchronized oscillatory activity and the directed information flow provide physiological basis for reverberation of memory items during maintenance. This points to a network for working memory that is bound by coherent oscillations involving cortical areas and hippocampus. SIGNIFICANCE STATEMENTHippocampal activity is known for its role in cognitive tasks involving episodic memory or spatial navigation, but its role in working memory and its sensitivity to workload is still under debate. Here, we investigated hippocampal and cortical activity while a subject maintained sets of letters in verbal working memory for a few seconds to guide action. After confirming the coupling between hippocampal oscillations and oscillations on the scalp, we found during maintenance that hippocampal oscillations increased coupling differentially to several areas of cortex by recording directly from the cortex.. During encoding of the letters, information flow was from auditory cortex to hippocampus and subsequently reversed during maintenance, thus providing a physiological basis for memory encoding and maintenance. This demonstrates a network for working memory that is bound by coherent oscillations that underlie the functional connectivity between cortical areas and hippocampus.

neuroscience↗

bioRxiv2018

Deep Convolutional modeling of human face selective columns reveals their role in pictorial face representation

Despite the massive accumulation of systems neuroscience findings, their functional meaning remains tentative, largely due to the absence of realistically performing models. The discovery that deep convolutional networks achieve human performance in realistic tasks offers fresh opportunities for such modeling. Here we show that the face-space topography of face-selective columns recorded intra-cranially in 32 patients significantly matches that of a DCNN having human-level face recognition capabilities. Three modeling aspects converge in pointing to a role of human face areas in pictorial rather than person identification: First, the match was confined to intermediate layers of the DCNN. Second, identity preserving image manipulations abolished the brain to DCNN correlation. Third, DCNN neurons matching face-column tuning displayed view-point selective receptive fields. Our results point to a \"convergent evolution\" of pattern similarities in biological and artificial face perception. They demonstrate DCNNs as a powerful modeling approach for deciphering the function of human cortical networks.

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bioRxiv2018

Phase resetting in human auditory cortex to visual speech

Natural conversation is multisensory: when we can see the speakers face, visual speech cues influence our perception of what is being said. The neuronal basis of this phenomenon remains unclear, though there is indication that phase modulation of neuronal oscillations--ongoing excitability fluctuations of neuronal populations in the brain--provides a mechanistic contribution. Investigating this question using naturalistic audiovisual speech with intracranial recordings in humans, we show that neuronal populations in auditory cortex track the temporal dynamics of unisensory visual speech using the phase of their slow oscillations and phase-related modulations in high-frequency activity. Auditory cortex thus builds a representation of the speech streams envelope based on visual speech alone, at least in part by resetting the phase of its ongoing oscillations. Phase reset could amplify the representation of the speech stream and organize the information contained in neuronal activity patterns. SIGNIFICANCE STATEMENTWatching the speaker can facilitate our understanding of what is being said. The mechanisms responsible for this influence of visual cues on the processing of speech remain incompletely understood. We studied those mechanisms by recording the human brains electrical activity through electrodes implanted surgically inside the skull. We found that some regions of cerebral cortex that process auditory speech also respond to visual speech even when it is shown as a silent movie without a soundtrack. This response can occur through a reset of the phase of ongoing oscillations, which helps augment the response of auditory cortex to audiovisual speech. Our results contribute to discover the mechanisms by which the brain merges auditory and visual speech into a unitary perception.

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bioRxiv2017

Repeated performance in problem-solving tasks attenuates human cortical responses

A ubiquitous characteristic of human cortical networks is their tendency to rapidly change their response properties upon repetition. While this phenomenon has been amply documented using simple sensory-motor tasks, it is still unclear to what extent brain activations change on a short time scale when we are engaged in high level, complex tasks. Here, we examined this question using three types of high-level visual problems. We analyzed data from intracranial recordings performed in eight patients, focusing on the location and type of changes and on their relationship to overt behavior. Our results show significant repetition effects, manifested as signal decrease with repetition, in three different groups of electrodes: Visual sites, which increased their activity during stimuli presentation; Processing Positive sites, which demonstrated increased activity throughout the experimental trial; and Processing Negative sites, which demonstrated suppression of activity during the trial as compared to baseline. Interestingly, despite these significant repetition effects, response time remained unchanged with repetition. These findings bear directly upon our ability to interpret results aggregated across multiple repetitions of the same complex task.

neuroscience↗

bioRxiv2017

Increasing Suppression Of Saccade-Related Transients Along The Human Visual Hierarchy

A key hallmark of visual perceptual awareness is robustness to instabilities arising from unnoticeable eye and eyelid movements. In previous human intracranial (iEEG) work (Golan et al., 2016) we found that excitatory broadband high-frequency activity transients, driven by eye blinks, are suppressed in higher-level but not early visual cortex. Here, we utilized the broad anatomical coverage of iEEG recordings in 12 eye-tracked neurosurgical patients to test whether a similar stabilizing mechanism operates following small saccades. We compared saccades (1.3{degrees}-3.7{degrees}) initiated during inspection of large individual visual objects with similarly-sized external stimulus displacements. Early visual cortex sites responded with positive transients to both conditions. In contrast, in both dorsal and ventral higher-level sites the response to saccades (but not to external displacements) was suppressed. These findings indicate that early visual cortex is highly unstable compared to higher-level visual regions which apparently constitute the main target of stabilizing extra-retinal oculomotor influences.

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