Biology subjects

Malach, R.

Publications and source records attributed to Malach, R..

At least 19 recordsLinked to original sources

bioRxiv2026

The Movie After-Effect: widespread adaptation of human cortex following naturalistic sensory experience

Neural systems adapt to prolonged sensory input through mechanisms such as gain control or homeostatic plasticity to maintain stable operating ranges. However, this phenomenon has so far been documented under extreme, non-ecological stimuli targeting specific sensory systems. Here, we reveal a widespread adaptation process across diverse human cortical regions following naturalistic movie watching conditions. The effect was evident in 218 out of 251 cortical regions (87%) that exhibit significant stimulus-driven activations. Analyzing the HCP fMRI data set in which 170 participants watched 14 movie clips, followed by rest periods - we found robust evidence for a movie-induced adaptation process, revealed in the post-movies rest periods. Within a region, voxels highly activated at the end of movies subsequently reduced their activity below baseline during rest, with the magnitude of this drop proportional to initial activation levels, manifested as a consistent voxel-population inversion effect. Conversely, persistently movie-inactivated voxels exhibited increased activation above baseline. Importantly, this Movie After-Effect (MvAE) enabled successful decoding of the specific rest periods following individual movie clips. Our findings suggest that under naturalistic conditions, cortical neurons dynamically change their gain to achieve homeostatic balance in a process akin to batch instance normalization in artificial neural networks. Whether this ubiquitous MvAE has additional cognitive and memory-related implications remains to be explored.

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bioRxiv2026

A cortical gradient of distance to criticality governs large-scale resting-state fMRI dynamics

The cortex generates a remarkable diversity of regional dynamics despite relying on broadly shared principles of recurrent organization. Here, we identify distance to criticality (DTC) as a unifying axis along which these dynamics are spatially organized. Analyzing resting-state fMRI BOLD signals and leveraging simple network models of randomly connected recurrent units, we show that DTC robustly explains key dynamical features, in particular, local power spectra and functional connectivity, across the full set of 360 cortical areas. Our analysis shows that a rank-order distribution of DTC values is highly conserved across subjects. Moreover, the empirical analysis of cortical slow dynamics and its fitted network simulations demonstrate similar power-laws across hierarchies of the cortical sheet. These results suggest that recurrent neuronal networks, operating close to criticality, can generate a remarkably rich dynamical repertoire which fit the entire range of experimentally observed cortical slow-timescale dynamics. Our findings underscore the importance of DTC as a powerful, fundamental generator underlying the spectrum of diverse cortical dynamics. HighlightsO_LISpontaneous (resting-state) activity in the human cortex is shown to be organized along a conserved spatial gradient of distance from criticality (DTC), with regions exhibiting a stable cross-individual rank order along this axis. C_LIO_LIMulti-subject fMRI data of regional power spectra and functional connectivity can be fitted with a single parameter simulation model based on DTC. C_LIO_LIQuantitative estimation of the DTC across cortical regions can be achieved using a simple sparse recurrent neural network model. C_LIO_LIThe model fits the power spectra of low frequency fluctuations and the distribution of functional connectivity. C_LIO_LIShape collapse analysis of the power spectrum demonstrates a universal profile across the resting cortex depending only on the DTC. C_LI

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bioRxiv2025

Axonal distribution of Layers IV-VI Connections in Human Visual Cortex Revealed by in-vitro extracellular injections of Biocytin.

The organization of interlaminar axonal connections was studied in slices of adult human visual association cortex. Cortical tissue was obtained during surgical glioma treatment in three subjects. Slices were injected with the highly sensitive anterograde tracer biocytin. In some cases, tract tracing was combined with laminar recordings of electrically evoked potentials, employing current-source density analysis. This study is based on 23 injections placed at various cortical layers and analyzed in detail. The results reveal a striking columnar architecture of local axons organized in vertically oriented bundles as well as vertical columns of neuronal cells bodies. A high degree of specificity was observed in the connectional patterns of various layers. This specificity was reflected in the tendency of lateral connections to spread into different cortical layers, and in the large variations in the axonal bouton densities in different layers. More specifically. Layer IV injections resulted in a more circular projection pattern including massive projections into layer II-III. Layer V injections produced extensive intra-laminar lateral connections while layer VI injections resulted in a vertical projection leading up to layer IV and a lateral intra-laminar projection. Thus, our results reveal highly specific connectional patterns in the different cortical layers in adult human association visual cortex.

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bioRxiv2024

The organization of high-level visual cortex is aligned with visual rather than abstract linguistic information

A fundamental question dominating the study of human visual cortex is whether it is organized along visual or semantic information. This question is unresolved, and the controversy has been rekindled by the recent report that surprisingly, revealed that the representations of textual description of images by linguistic artificial networks successfully predict the response of high-level visual cortex to visual images. These findings appear to support a linguistic, abstract, organizing principle of human visual cortex. Here, using iEEG recordings from high level visual cortex in patients, we contributed to this debate, by testing the hypothesis that this linguistic alignment is restricted to textual descriptions of the visual content of the images (visual text) and does not extend to abstract textual descriptions (abstract text). We selected images that depict familiar faces and places, as these images allow for the best dissociation between these two types of text and generated their visual and abstract (e.g., name and biography of a person) textual descriptions. We then predicted the relational structures of the iEEG response to the images using their textual representations based on a large language model and the image representation based on a convolutional neural network. Neural relational-structures in high-level visual cortex were similarly predicted by images and visual-text but not abstract-text representations. Abstract text best predicted responses of the fronto-parietal cortex to the images. These results demonstrate that visual-language alignment in high-level visual cortex is limited to visually grounded language.

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bioRxiv2024

Text-related functionality of visual human pre-frontal activations revealed through neural network convergence

The functional role of visual activations of human pre-frontal cortex remains a deeply debated question. Its significance extends to fundamental issues of functional localization and global theories of consciousness. Here we addressed this question by comparing, dynamically, the potential parallels between the relational structure of prefrontal visual activations and visual and textual-trained deep neural networks (DNNs). The frontal visual relational structures were revealed in intra-cranial recordings of human patients, conducted for clinical purposes, while the patients viewed familiar images of faces and places. Our results reveal that visual relational structures in frontal cortex were, surprisingly, predicted by text and not visual DNNs. Importantly, the temporal dynamics of these correlations showed striking differences, with a rapid decline over time for the visual component, but persistent dynamics including a significant image offset response for the text component. The results point to a dynamic text-related function of visual prefrontal responses in the human brain.

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bioRxiv2023

Hippocampal Ripples linked to Declarative Memory Judgments in Children

Intracranial studies have demonstrated significant roles for hippocampal ripples in human declarative memory. Yet, the developmental trajectory and contribution of ripples to memory processes in children remain unknown. We studied hippocampal ripple activity using intracranial recordings in 14 children (age: 6-14) undergoing epilepsy monitoring. After watching a pink panther cartoon twice, participants engaged in an old/new recognition test, determining whether events portrayed in short (4s) videoclips stemmed from the cartoon they had just viewed. Our results reveal a significant rise in ripple rate during successful recognition of familiar events. An anticipatory decline in ripple rate preceded recognition errors. Interestingly, when participants viewed the cartoon passively during the initial full-length screenings, the overall temporal pattern of ripple activation remained consistent across repetitions, and significantly distinct from explicit recognition. We conclude that hippocampal ripples in children play a key role in declarative memory, supporting the explicit identification of previously encountered events.

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bioRxiv2023

Modulation of proximity to criticality enhances slow activity fluctuations during free recall

Ultra-slow fluctuations are a hallmark of spontaneous cortical activity. We examine the hypothesis that these unique dynamics arise from recurrent neuronal networks operating near a phase transition, a state characterized by critical slowing down. A further prediction of such dynamics is that a small modulation towards the critical transition should lead to specific amplification of slow fluctuations. Here, we relate this phenomenon to experimental findings using a simulation of a simple random recurrent network. Importantly, the model aligns with direct intracranial electroencephalography recordings from human visual cortex during both rest and visual free-recall, specifically replicating the observed enhancement of slow fluctuations during free recall. These simulations illuminate a simple and powerful mechanism underlying slow spontaneous fluctuations, while enabling the rapid transition between different spontaneous states. They propose that modulation towards criticality might be a universal strategy employed by cortical networks to engage in a spontaneous generative mode.

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bioRxiv2022

Perceptual stability reflected in neuronal pattern similarities in human visual cortex

The magnitude of neuronal activation is commonly considered a critical factor for conscious perception of visual content. However, this dogma contrasts with the phenomenon of rapid adaptation, in which the magnitude of neuronal activation drops dramatically in a rapid manner, while the visual stimulus and the conscious experience it elicits remain stable. Here we report that the profiles of multi-site activation patterns and their relational geometry -i.e. the similarity distances between activation patterns, as revealed using iEEG recordings, are sustained during extended stimulation despite the major magnitude decrease. These results are compatible with the hypothesis that conscious perceptual content is associated with the neuronal pattern profiles and their similarity distances, rather than by the overall activation magnitude, in human visual cortex.

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bioRxiv2022

Retrospective behavioral sampling (RBS): a method to effectively track the cognitive fluctuations driven by naturalistic stimulation

Everyday experiences are dynamic, driving fluctuations across simultaneous cognitive processes. A key challenge in the study of naturalistic cognition is to disentangle the complexity of these dynamic processes, without altering the natural experience itself. Retrospective behavioral sampling (RBS) is a novel approach to track the cognitive fluctuations throughout the time-course of naturalistic stimulation, across a variety of cognitive dimensions. We tested the effectiveness and reliability of RBS in a web-based experiment, in which 53 participants viewed short movies and listened to a story, followed by retrospective reporting. Participants recalled their experience of 55 discrete events from the stimuli, rating their quality of memory, magnitude of surprise, intensity of negative and positive emotions, perceived importance, reflectivity state, and mental time travel. In addition, a subset of the original cohort re-rated their memory of events in a follow-up questionnaire. Results show highly replicable fluctuation patterns across distinct cognitive dimensions, thereby revealing a stimulus-driven experience that is substantially shared among individuals. Remarkably, memory ratings more than a week after stimulation resulted in an almost identical time-course of memorability as measured immediately following stimulation. In addition, idiosyncratic response patterns were preserved across different stimuli, indicating that RBS characterizes individual differences that are stimulus invariant. The current findings highlight the potential of RBS as a powerful tool for measuring dynamic processes of naturalistic cognition. We discuss the promising approach of matching RBS fluctuations with dynamic processes measured via other testing modalities, such as neuroimaging, to study the neural manifestations of naturalistic cognitive processing.

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bioRxiv2020

The Surprising Role of the Default Mode Network

The default mode network (DMN) is a group of high-order brain regions recently implicated in processing external naturalistic events, yet it remains unclear what cognitive function it serves. Here we identified the cognitive states predictive of DMN fMRI coactivation. Particularly, we developed a state-fluctuation pattern analysis, matching network coactivations across a short movie with retrospective behavioral sampling of movie events. Network coactivation was selectively correlated with the state of surprise across movie events, compared to all other cognitive states (e.g. emotion, vividness). The effect was exhibited in the DMN, but not dorsal attention or visual networks. Furthermore, surprise was found to mediate DMN coactivations with hippocampus and nucleus accumbens. These unexpected findings point to the DMN as a major hub in high-level prediction-error representations.

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bioRxiv2020

Resting state fluctuations underlie free and creative verbal behaviors in the human brain

Internally generated (free) ideas and creative thoughts constitute a fundamentally important aspect of the human experience, yet the neuronal mechanism driving these behaviors remains elusive. Here we examined the hypothesis that the common mechanism underlying free verbal behaviors is the ultra-slow activity fluctuations (termed "resting state fluctuations") that emerge spontaneously in the human brain. In our experiment, participants were asked to perform three voluntary verbal tasks: a verbal fluency task, a verbal creativity task (alternative uses of everyday objects) and a divergent thinking task (instances of common concepts), during fMRI scanning. BOLD-activity during these tasks was contrasted with a control-deterministic verbal task, in which the behavior was fully determined by external stimuli. Our results reveal that in all three voluntary tasks, the verbal-generation responses displayed a gradual anticipatory buildup that preceded the deterministic control-related responses by [~]2 seconds. Importantly, variance analysis ruled out a time-jittered step-function response confound. Critically, the waveforms of the anticipatory buildups, as reflected in their time-frequency dynamics, were significantly correlated to the dynamics of resting state fluctuations, measured during a rest period prior to the tasks. Specifically, the amplitude of low frequency fluctuations (fALFF) of the resting state time-course and the voluntary verbal responses in the left inferior frontal gyrus (LH IFG), a central hub engaged in these tasks, were correlated across individual participants. This correlation was not a general BOLD-related or verbal-response related result, as it was not found during the externally-determined verbal control condition. Furthermore, it was specific to brain regions known to be involved in language production. These results indicate that the slow buildup preceding voluntary behaviors is linked to resting state fluctuations. Thus, these ubiquitous brain fluctuations may constitute a common neural mechanism underlying the generation of free and creative behaviors in the human brain.

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bioRxiv2019

Studying the precuneus reveals structure-function-affect correlation in long-term meditators

Understanding the relationship between brain structure, function and self-reports has hardly been addressed until now in meditation research. Here we demonstrate such relationship, using Mindfulness meditation (MM). MM aims to reduce thought-related processes and enhance bodily awareness, thereby reducing identification with thought content and deconstructing maladaptive self-schema. We thus hypothesized that structure of the default mode network (DMN) regions, associated with spontaneous thoughts and self-representation, would negatively correlate with MM experience and self-reported positive affect, while positively correlating with DMN resting-state function.\n\nCross-sectionally comparing a unique group of adept MM practitioners and meditation-naive matched controls using voxel based morphometry revealed that gray matter (GM) density of the left precuneus (L-Prc) was negatively correlated with MM expertise. Furthermore, GM density of the L-Prc was positively correlated with resting state and task related functional (fMRI) measures within the L-Prc in the MM practitioners, but not in the controls. Finally, the L-Prcs GM density negatively correlated with positive affect across all participants.\n\nOur findings may shed light on understanding structure-function-self reports relationship. While our approach enables studying suggestive correlations in expert MM practitioners, longitudinal studies are required for direct insights concerning the question of causality.\n\nSignificance statementUnderstanding the relationship between brain structure and function, individual differences and self-reports, is an important goal of neuroscience. Yet, these factors were hardly investigated together in meditation research. The precuneus is part of the default mode network (DMN) involved in thought related processes. Mindfulness meditation (MM) is a mental practice aiming to reduce thought related processes. Here, by cross-sectionally comparing adept meditators and controls, we found that in the precuneus of MM practitioners, structure associated with function. Overall, structure negatively correlated with practice length, as well as with positive affect scores. The structure-function correlation was only significant in the meditators group, possibly implying that prolonged meditation improved structure and function attunement in the DMN. More generally, this study demonstrates that mental practice can be related to conjoint structural and functional effects, as well as to affective self-reports.

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bioRxiv2019

Inter-thinker consistency of language activations during abstract thoughts

Human brain imaging typically employs structured and controlled tasks to avoid variable and inconsistent activation patterns. Here we argue against this assumption by showing that an extremely open-ended, high level cognitive task-loosely defined as "abstract thinking" leads to a precise, and highly consistent activation maps. Thus we show that activation maps generated during such cognitive process were precisely located relative to borders of well-known networks such as internal speech, visual and motor imagery. The activation patterns allowed decoding the thought condition at >95%. Surprisingly, the activated networks remained the same regardless of changes in thought content. Finally, we found a remarkably consistent activation map across individuals engaged in abstract thinking. The activation to abstract thinking bordered, but strictly avoided visual and motor networks. On the other hand, it partly overlapped with left lateralized language networks. These observations were supported by a quantitative neuronal distance metric analysis. Our results reveal that despite its high level, and varied content nature-abstract thinking activates surprisingly precise and consistent networks in the participants brains. Thinker refers to: The agent of thought; Intellectual, one who tries to use his or her intellect to work, study, reflect, speculate on, or ask and answer questions with regard to a variety of different ideas" (Wikipedia).

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bioRxiv2018

Where does time go when you blink?

Retinal input is frequently lost due to eye blinks, yet humans rarely notice these gaps in visual input. While previous studies focused on the psychophysical and neural correlates of diminished awareness to blinks, the impact of blinks on the perceived time of concurrent events is unknown. Here, we investigated whether the subjective sense of time is altered by spontaneous eye blinks, and how this link may inform mechanisms of time perception. We found that participants significantly underestimated the duration of a visual stimulus when a blink occurred during the stimulus. Importantly, this effect was not present when durations of an auditory stimulus were judged. These results point to a link between spontaneous blinks, previously demonstrated to induce suppression of activity in early visual cortex, and a compression of subjective time. The findings suggest that ongoing encoding within modality-specific sensory cortices, independent of conscious awareness, inform the subjective sense of time.

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bioRxiv2018

Face-selective units in human ventral temporal cortex reactivate during free recall

Properties of face-responsive individual neurons in the human ventral temporal cortex (VTC) have yet to be studied, and their role in conscious perception remains unknown. To explore this, we implanted microelectrodes into the VTCs of eight human subjects undergoing invasive epilepsy monitoring. Most (26 of 33) category-selective units showed specificity for face stimuli, with a range of response profiles. Different face exemplars evoked consistent and discriminable responses in the population of units sampled. During a free recall task, face-selective units selectively reactivated in the absence of visual stimulation during the 2-second window prior to face recall events. Furthermore, the identity of the recalled face could be predicted by comparing activity preceding recall events to activity evoked by visual stimulation.

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bioRxiv2018

Widespread suppression of high-order visual cortex during blinks and external predictable visual interruptions

Spontaneous eye blinks generate frequent potent interruptions to the retinal input and yet go unnoticed. As such, they provide an attractive approach to the study of the neural correlates of visual awareness. Here, we tested the potential role of predictability in generating blink-related effects using fMRI. While participants attentively watched still images of faces and houses, we monitored naturally occurring spontaneous blinks and introduced three kinds of matched visual interruptions: cued voluntary blinks, self-initiated (and hence, predictable) external darkenings, and physically similar but unpredictable external darkenings. These events impact was inspected using fMRI across the visual hierarchy. In early visual cortex, both spontaneous and voluntary blinks, as well as predictable and unpredictable external darkenings, led to largely similar positive responses in peripheral representations. In mid- and high-level visual cortex, all predictable conditions (spontaneous blinks, voluntary blinks, and self-initiated external darkenings) were associated with signal decreases. In contrast, unpredictable darkenings were associated with signal increases. These findings suggest that general-purpose prediction-related mechanisms are involved in producing a small but widespread suppression of mid- and high-order visual regions during blinks. Such suppression may down-regulate responses to predictable transients in the human visual hierarchy.

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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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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.

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