@BOOK{Lifshitz2018-yb, title = "Cultural neurophenomenology of psychedelic thought", author = "Lifshitz, Michael and Sheiner, Eli and Kirmayer, Laurence J", editor = "Christoff, Kalina and Fox, Kieran C R", publisher = "Oxford University Press", abstract = "This chapter explores psychedelics as catalysts of spontaneous thought. Classic serotonergic psychedelics such as psilocybin, LSD, and ayahuasca can induce potent alterations in cognition and perception. The chapter reviews research on these substances through the lens of cultural neurophenomenology, which aims to trace how neurobiology and sociocultural factors interact to shape experience. After a decades-long hiatus, the scientific study of psychedelics is rediscovering the potential of these substances to promote creative insight, evoke mystical experiences, and improve clinical outcomes. Moreover, neuroimaging experiments have begun to unravel the influence of psychedelics on large-scale connectivity networks of the human brain. Tapping perspectives from the social sciences, the chapter underscores how culture and context constrain the flexible cognitive states brought about by psychedelics. This integrative approach suggests that seemingly spontaneous psychedelic thought patterns reflect a complex interaction of biological, cognitive, and cultural factors—from pharmacology and brain function to ritual, belief, and expectation.", month = "5~" # apr, year = 2018, keywords = "RePhD;psychedelics;mysticism;meditation", doi = "10.1093/oxfordhb/9780190464745.013.4", language = "en" } @ARTICLE{Lifshitz2019-in, title = "Mindfulness-based therapy regulates brain connectivity in major depression", author = "Lifshitz, Michael and Sacchet, Matthew D and Huntenburg, Julia M and Thiery, Thomas and Fan, Yan and Gärtner, Matti and Grimm, Simone and Winnebeck, Emilia and Fissler, Maria and Schroeter, Titus A and Margulies, Daniel S and Barnhofer, Thorsten", journal = "Psychother. Psychosom.", publisher = "S. Karger AG", volume = 88, number = 6, pages = "375--377", month = "11~" # sep, year = 2019, keywords = "Frontoparietal network; Functional connectivity; Major depression; Mindfulness-based therapy; Nonpharmacological intervention;RePhD;meditation;depression;fMRI Attention", doi = "10.1159/000501170", language = "en" } @ARTICLE{Lifshitz2020-sd, title = "The understudied side of contemplation: Words, images, and intentions in a syncretic spiritual practice", author = "Lifshitz, Michael and Brahinsky, Joshua and Luhrmann, T M", journal = "Int. J. Clin. Exp. Hypn.", publisher = "Informa UK Limited", volume = 68, number = 2, pages = "183--199", abstract = "The science of contemplation has focused on mindfulness in a manner quite disproportionate to its use in contemplative traditions. Mindfulness, as understood within the scientific community, is a practice that invites practitioners to disattend to words and images. The practitioner is meant to experience things as they ``really are,'' unfolding here and now in the flux of embodied sensations. Yet the use of words and images, together with intentions, is a far more common contemplative practice. The authors present ethnographic research with a syncretic contemplative tradition, Integral Transformative practice (ITP), which grew out of the Human Potential Movement of the 1960s. The authors focus on the practice of ``affirmations,'' in which practitioners seek to actualize spiritual goals by imagining future possibilities. Our ethnographic account invites new avenues for psychological research to illuminate the role of words and images in contemplation.", month = "2~" # apr, year = 2020, keywords = "RePhD;mysticism", doi = "10.1080/00207144.2020.1726180", language = "en" } @ARTICLE{Gramfort2013-hm, title = "{MEG} and {EEG} data analysis with {MNE}-Python", author = "Gramfort, Alexandre and Luessi, Martin and Larson, Eric and Engemann, Denis A and Strohmeier, Daniel and Brodbeck, Christian and Goj, Roman and Jas, Mainak and Brooks, Teon and Parkkonen, Lauri and Hämäläinen, Matti", journal = "Front. Neurosci.", publisher = "Frontiers Media SA", volume = 7, pages = 267, abstract = "Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals generated by neuronal activity in the brain. Using these signals to characterize and locate neural activation in the brain is a challenge that requires expertise in physics, signal processing, statistics, and numerical methods. As part of the MNE software suite, MNE-Python is an open-source software package that addresses this challenge by providing state-of-the-art algorithms implemented in Python that cover multiple methods of data preprocessing, source localization, statistical analysis, and estimation of functional connectivity between distributed brain regions. All algorithms and utility functions are implemented in a consistent manner with well-documented interfaces, enabling users to create M/EEG data analysis pipelines by writing Python scripts. Moreover, MNE-Python is tightly integrated with the core Python libraries for scientific comptutation (NumPy, SciPy) and visualization (matplotlib and Mayavi), as well as the greater neuroimaging ecosystem in Python via the Nibabel package. The code is provided under the new BSD license allowing code reuse, even in commercial products. Although MNE-Python has only been under heavy development for a couple of years, it has rapidly evolved with expanded analysis capabilities and pedagogical tutorials because multiple labs have collaborated during code development to help share best practices. MNE-Python also gives easy access to preprocessed datasets, helping users to get started quickly and facilitating reproducibility of methods by other researchers. Full documentation, including dozens of examples, is available at http://martinos.org/mne.", month = "26~" # dec, year = 2013, keywords = "electroencephalography (EEG); magnetoencephalography (MEG); neuroimaging; open-source; python; software;RePhD;EEG;preprocessing", doi = "10.3389/fnins.2013.00267", language = "en" } @ARTICLE{Rogasch2014-sf, title = "Removing artefacts from {TMS}-{EEG} recordings using independent component analysis: importance for assessing prefrontal and motor cortex network properties", author = "Rogasch, Nigel C and Thomson, Richard H and Farzan, Faranak and Fitzgibbon, Bernadette M and Bailey, Neil W and Hernandez-Pavon, Julio C and Daskalakis, Zafiris J and Fitzgerald, Paul B", journal = "Neuroimage", publisher = "Elsevier BV", volume = 101, pages = "425--439", abstract = "INTRODUCTION: The combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG) is emerging as a powerful tool for causally investigating cortical mechanisms and networks. However, various artefacts contaminate TMS-EEG recordings, particularly over regions such as the dorsolateral prefrontal cortex (DLPFC). The aim of this study was to substantiate removal of artefacts from TMS-EEG recordings following stimulation of the DLPFC and motor cortex using independent component analysis (ICA). METHODS: 36 healthy volunteers (30.8 ± 9 years, 9 female) received 75 single TMS pulses to the left DLPFC or left motor cortex while EEG was recorded from 57 electrodes. A subset of 9 volunteers also received 50 sham pulses. The large TMS artefact and early muscle activity (-2 to ~15 ms) were removed using interpolation and the remaining EEG signal was processed in two separate ICA runs using the FastICA algorithm. Five sub-types of TMS-related artefacts were manually identified: remaining muscle artefacts, decay artefacts, blink artefacts, auditory-evoked potentials and other noise-related artefacts. The cause of proposed blink and auditory-evoked potentials was assessed by concatenating known artefacts (i.e. voluntary blinks or auditory-evoked potentials resulting from sham TMS) to the TMS trials before ICA and evaluating grouping of resultant independent components (ICs). Finally, we assessed the effect of removing specific artefact types on TMS-evoked potentials (TEPs) and TMS-evoked oscillations. RESULTS: Over DLPFC, ICs from proposed muscle and decay artefacts correlated with TMS-evoked muscle activity size, whereas proposed TMS-evoked blink ICs combined with voluntary blinks and auditory ICs with auditory-evoked potentials from sham TMS. Individual artefact sub-types characteristically distorted each measure of DLPFC function across the scalp. When free of artefact, TEPs and TMS-evoked oscillations could be measured following DLPFC stimulation. Importantly, characteristic TEPs following motor cortex stimulation (N15, P30, N45, P60, N100) could be recovered from artefactual data, corroborating the reliability of ICA-based artefact correction. CONCLUSIONS: Various different artefacts contaminate TMS-EEG recordings over the DLPFC and motor cortex. However, these artefacts can be removed with apparent minimal impact on neural activity using ICA, allowing the study of TMS-evoked cortical network properties.", month = "1~" # nov, year = 2014, keywords = "Artefacts; Dorsolateral prefrontal cortex; Electroencephalography; Independent component analysis; Motor cortex; Transcranial magnetic stimulation;RePhD;EEG;preprocessing", doi = "10.1016/j.neuroimage.2014.07.037", language = "en" } @ARTICLE{Zapata2024-ox, title = "Automatic sleep spindles identification and classification with multitapers and convolution", author = "Zapata, Ignacio A and Wen, Peng and Jones, Evan and Fjaagesund, Shauna and Li, Yan", journal = "Sleep", publisher = "Oxford University Press (OUP)", volume = 47, number = 1, pages = "zsad159", abstract = "Sleep spindles are isolated transient surges of oscillatory neural activity present during sleep stages 2 and 3 in the nonrapid eye movement (NREM). They can indicate the mechanisms of memory consolidation and plasticity in the brain. Spindles can be identified across cortical areas and classified as either slow or fast. There are spindle transients across different frequencies and power, yet most of their functions remain a mystery. Using several electroencephalogram (EEG) databases, this study presents a new method, called the ``spindles across multiple channels'' (SAMC) method, for identifying and categorizing sleep spindles in EEGs during the NREM sleep. The SAMC method uses a multitapers and convolution (MT\&C) approach to extract the spectral estimation of different frequencies present in sleep EEGs and graphically identify spindles across multiple channels. The characteristics of spindles, such as duration, power, and event areas, are also extracted by the SAMC method. Comparison with other state-of-the-art spindle identification methods demonstrated the superiority of the proposed method with an agreement rate, average positive predictive value, and sensitivity of over 90\% for spindle classification across the three databases used in this paper. The computing cost was found to be, on average, 0.004 seconds per epoch. The proposed method can potentially improve the understanding of the behavior of spindles across the scalp and accurately identify and categories sleep spindles.", month = "11~" # jan, year = 2024, keywords = "multitapers; sleep EEG; sleep spindles; spectra density estimation (SDE); spectral estimation;RePhD;RePhD/gradCPT;EEG", doi = "10.1093/sleep/zsad159", language = "en" } @ARTICLE{Kerr2013-qp, title = "Mindfulness starts with the body: somatosensory attention and top-down modulation of cortical alpha rhythms in mindfulness meditation", author = "Kerr, Catherine E and Sacchet, Matthew D and Lazar, Sara W and Moore, Christopher I and Jones, Stephanie R", journal = "Front. Hum. Neurosci.", publisher = "frontiersin.org", volume = 7, year = 2013, keywords = "RePhD", doi = "10.3389/fnhum.2013.00012" } @ARTICLE{Rosenberg2013-nl, title = "Sustaining visual attention in the face of distraction: a novel gradual-onset continuous performance task", author = "Rosenberg, Monica and Noonan, Sarah and DeGutis, Joseph and Esterman, Michael", journal = "Atten. Percept. Psychophys.", publisher = "Springer Science and Business Media LLC", volume = 75, number = 3, pages = "426--439", abstract = "Sustained attention is a fundamental aspect of human cognition and has been widely studied in applied and clinical contexts. Despite a growing understanding of how attention varies throughout task performance, moment-to-moment fluctuations are often difficult to assess. In order to better characterize fluctuations in sustained visual attention, in the present study we employed a novel continuous performance task (CPT), the gradual-onset CPT (gradCPT). In the gradCPT, a central face stimulus gradually transitions between individuals at a constant rate (1,200 ms), and participants are instructed to respond to each male face but not to a rare target female face. In the distractor-present version, the background distractors consist of scene images, and in the distractor-absent condition, of phase-scrambled scene images. The results confirmed that the gradCPT taxes sustained attention, as vigilance decrements were observed over the task's 12-min duration: Participants made more commission errors and showed increasingly variable response latencies (RTs) over time. Participants' attentional states also fluctuated from moment to moment, with periods of higher RT variability being associated with increased likelihood of errors and greater speed-accuracy trade-offs. In addition, task performance was related to self-reported mindfulness and the propensity for attention lapses in everyday life. The gradCPT is a useful tool for studying both low- and high-frequency fluctuations in sustained visual attention and is sensitive to individual differences in attentional ability.", month = "9~" # apr, year = 2013, keywords = "RePhD;RePhD/gradCPT;attention", doi = "10.3758/s13414-012-0413-x", language = "en" } @ARTICLE{Fortenbaugh2018-vk, title = "Tracking behavioral and neural fluctuations during sustained attention: A robust replication and extension", author = "Fortenbaugh, Francesca C and Rothlein, David and McGlinchey, Regina and DeGutis, Joseph and Esterman, Michael", journal = "Neuroimage", publisher = "Neuroimage", volume = 171, pages = "148--164", abstract = "Novel paradigms have allowed for more precise measurements of sustained attention ability and fluctuations in sustained attention over time, as well as the neural basis of fluctuations and lapses in performance. However, in recent years, concerns have arisen over the replicability of neuroimaging studies and psychology more broadly, particularly given the typically small sample sizes. One recently developed paradigm, the gradual-onset continuous performance task (gradCPT) has been validated behaviorally in large samples of participants. Yet neuroimaging studies investigating the neural basis of performance on this task have only been collected in small samples. The present study completed both a robust replication of the original neuroimaging findings and extended previous results from the gradCPT task using a large sample of 140 Veteran participants. Results replicate findings that fluctuations in attentional stability are tracked over time by BOLD activity in task positive (e.g., dorsal and ventral attention networks) and task negative (e.g., default network) regions. Extending prior results, we relate this coupling between attentional stability and on-going brain activity to overall sustained attention ability and demonstrate that this coupling strength, along with across-network coupling, could be used to predict individual differences in performance. Additionally, the results extend previous findings by demonstrating that temporal dynamics across the default and dorsal attention networks are associated with lapse-likelihood on subsequent trials. This study demonstrates the reliability of the gradCPT, and underscores the utility of this paradigm in understanding attentional fluctuations, as well as individual variation and deficits in sustained attention.", month = "1~" # may, year = 2018, keywords = "Continuous performance task; Default mode network; Dorsal attention network; Vigilance; fMRI;RePhD;RePhD/unread;RePhD/gradCPT;fMRI Attention;meditation;attention", doi = "10.1016/j.neuroimage.2018.01.002", language = "en" } @ARTICLE{Agrawal2024-el, title = "Nothingness in meditation: Making sense of emptiness and cessation", author = "Agrawal, Vismay and Laukkonen, Ruben Eero", journal = "PsyArXiv", abstract = "Contemplative practices have been shown to elicit a range of experiences and insights often referred to as ``nothingness''. However, these encounters are frequently conflated and remain undifferentiated. Here we address this ambiguity and provide a nuanced understanding of two such events: 1) emptiness (lack of inherent existence in experience, i.e., no-thingness) and 2) cessation (“cut” or absence in the stream of consciousness, i.e., nothingness). We synthesize insights from Buddhist literature and empirical research, investigating the relationship between these “nothingness” phenomena, their transformative effects, and neural correlates. We also examine multiple pathways that may lead to cessation and consider potential cognitive models underlying these experiences using the active inference framework. Finally, we discuss the relationship between “nothingness” events and cessation of suffering, setting the stage for further development in this field. Our unique contributions involve juxtaposing various experiences of “void, oneness, non-dual awareness, pure consciousness” with insights into “emptiness and cessation”, and analyzing their potential implications for alleviating suffering.", month = "18~" # mar, year = 2024, keywords = "RePhD;meditation", doi = "10.31234/osf.io/tygdf" } @ARTICLE{Geniesse2019-ae, title = "Generating dynamical neuroimaging spatiotemporal representations ({DyNeuSR}) using topological data analysis", author = "Geniesse, Caleb and Sporns, Olaf and Petri, Giovanni and Saggar, Manish", journal = "Netw. Neurosci.", publisher = "MIT Press - Journals", volume = 3, number = 3, pages = "763--778", abstract = "In this article, we present an open source neuroinformatics platform for exploring, analyzing, and validating distilled graphical representations of high-dimensional neuroimaging data extracted using topological data analysis (TDA). TDA techniques like Mapper have been recently applied to examine the brain's dynamical organization during ongoing cognition without averaging data in space, in time, or across participants at the outset. Such TDA-based approaches mark an important deviation from standard neuroimaging analyses by distilling complex high-dimensional neuroimaging data into simple-yet neurophysiologically valid and behaviorally relevant-representations that can be interactively explored at the single-participant level. To facilitate wider use of such techniques within neuroimaging and general neuroscience communities, our work provides several tools for visualizing, interacting with, and grounding TDA-generated graphical representations in neurophysiology. Through Python-based Jupyter notebooks and open datasets, we provide a platform to assess and visualize different intermittent stages of Mapper and examine the influence of Mapper parameters on the generated representations. We hope this platform could enable researchers and clinicians alike to explore topological representations of neuroimaging data and generate biological insights underlying complex mental disorders.", month = "1~" # jul, year = 2019, keywords = "Brain dynamics; Brain networks; Mapper; TDA; fMRI;RePhD;RePhD/unread;MRI Methods", doi = "10.1162/netn\_a\_00093", language = "en" } @ARTICLE{Saggar2012-yb, title = "Intensive training induces longitudinal changes in meditation state-related {EEG} oscillatory activity", author = "Saggar, Manish and King, Brandon G and Zanesco, Anthony P and Maclean, Katherine A and Aichele, Stephen R and Jacobs, Tonya L and Bridwell, David A and Shaver, Phillip R and Rosenberg, Erika L and Sahdra, Baljinder K and Ferrer, Emilio and Tang, Akaysha C and Mangun, George R and Wallace, B Alan and Miikkulainen, Risto and Saron, Clifford D", journal = "Front. Hum. Neurosci.", publisher = "Frontiers Media SA", volume = 6, pages = 256, abstract = "The capacity to focus one's attention for an extended period of time can be increased through training in contemplative practices. However, the cognitive processes engaged during meditation that support trait changes in cognition are not well characterized. We conducted a longitudinal wait-list controlled study of intensive meditation training. Retreat participants practiced focused attention (FA) meditation techniques for three months during an initial retreat. Wait-list participants later undertook formally identical training during a second retreat. Dense-array scalp-recorded electroencephalogram (EEG) data were collected during 6 min of mindfulness of breathing meditation at three assessment points during each retreat. Second-order blind source separation, along with a novel semi-automatic artifact removal tool (SMART), was used for data preprocessing. We observed replicable reductions in meditative state-related beta-band power bilaterally over anteriocentral and posterior scalp regions. In addition, individual alpha frequency (IAF) decreased across both retreats and in direct relation to the amount of meditative practice. These findings provide evidence for replicable longitudinal changes in brain oscillatory activity during meditation and increase our understanding of the cortical processes engaged during meditation that may support long-term improvements in cognition.", month = "10~" # sep, year = 2012, keywords = "EEG; attention; beta; individual alpha frequency; meditation; training;RePhD;RePhD/unread;EEG;meditation", doi = "10.3389/fnhum.2012.00256", language = "en" } @ARTICLE{Saggar2018-yi, title = "Towards a new approach to reveal dynamical organization of the brain using topological data analysis", author = "Saggar, Manish and Sporns, Olaf and Gonzalez-Castillo, Javier and Bandettini, Peter A and Carlsson, Gunnar and Glover, Gary and Reiss, Allan L", journal = "Nat. Commun.", publisher = "Nature Publishing Group", volume = 9, number = 1, pages = 1399, abstract = "Little is known about how our brains dynamically adapt for efficient functioning. Most previous work has focused on analyzing changes in co-fluctuations between a set of brain regions over several temporal segments of the data. We argue that by collapsing data in space or time, we stand to lose useful information about the brain's dynamical organization. Here we use Topological Data Analysis to reveal the overall organization of whole-brain activity maps at a single-participant level-as an interactive representation-without arbitrarily collapsing data in space or time. Using existing multitask fMRI datasets, with the known ground truth about the timing of transitions from one task-block to next, our approach tracks both within- and between-task transitions at a much faster time scale (~4-9 s) than before. The individual differences in the revealed dynamical organization predict task performance. In summary, our approach distills complex brain dynamics into interactive and behaviorally relevant representations.", month = "11~" # apr, year = 2018, keywords = "RePhD;RePhD/unread;MRI Methods", doi = "10.1038/s41467-018-03664-4", language = "en" } @ARTICLE{Siebenhuhner2020-kt, title = "Genuine cross-frequency coupling networks in human resting-state electrophysiological recordings", author = "Siebenhühner, Felix and Wang, Sheng H and Arnulfo, Gabriele and Lampinen, Anna and Nobili, Lino and Palva, J Matias and Palva, Satu", journal = "PLoS Biol.", publisher = "Public Library of Science (PLoS)", volume = 18, number = 5, pages = "e3000685", abstract = "Phase synchronization of neuronal oscillations in specific frequency bands coordinates anatomically distributed neuronal processing and communication. Typically, oscillations and synchronization take place concurrently in many distinct frequencies, which serve separate computational roles in cognitive functions. While within-frequency phase synchronization has been studied extensively, less is known about the mechanisms that govern neuronal processing distributed across frequencies and brain regions. Such integration of processing between frequencies could be achieved via cross-frequency coupling (CFC), either by phase-amplitude coupling (PAC) or by n:m-cross-frequency phase synchrony (CFS). So far, studies have mostly focused on local CFC in individual brain regions, whereas the presence and functional organization of CFC between brain areas have remained largely unknown. We posit that interareal CFC may be essential for large-scale coordination of neuronal activity and investigate here whether genuine CFC networks are present in human resting-state (RS) brain activity. To assess the functional organization of CFC networks, we identified brain-wide CFC networks at mesoscale resolution from stereoelectroencephalography (SEEG) and at macroscale resolution from source-reconstructed magnetoencephalography (MEG) data. We developed a novel, to our knowledge, graph-theoretical method to distinguish genuine CFC from spurious CFC that may arise from nonsinusoidal signals ubiquitous in neuronal activity. We show that genuine interareal CFC is present in human RS activity in both SEEG and MEG data. Both CFS and PAC networks coupled theta and alpha oscillations with higher frequencies in large-scale networks connecting anterior and posterior brain regions. CFS and PAC networks had distinct spectral patterns and opposing distribution of low- and high-frequency network hubs, implying that they constitute distinct CFC mechanisms. The strength of CFS networks was also predictive of cognitive performance in a separate neuropsychological assessment. In conclusion, these results provide evidence for interareal CFS and PAC being 2 distinct mechanisms for coupling oscillations across frequencies in large-scale brain networks.", month = may, year = 2020, keywords = "RePhD;RePhD/unread;EEG", doi = "10.1371/journal.pbio.3000685", language = "en" } @ARTICLE{Zang2004-qw, title = "Regional homogeneity approach to {fMRI} data analysis", author = "Zang, Yufeng and Jiang, Tianzi and Lu, Yingli and He, Yong and Tian, Lixia", journal = "Neuroimage", publisher = "Elsevier BV", volume = 22, number = 1, pages = "394--400", abstract = "Kendall's coefficient concordance (KCC) can measure the similarity of a number of time series. It has been used for purifying a given cluster in functional MRI (fMRI). In the present study, a new method was developed based on the regional homogeneity (ReHo), in which KCC was used to measure the similarity of the time series of a given voxel to those of its nearest neighbors in a voxel-wise way. Six healthy subjects performed left and right finger movement tasks in event-related design; five of them were additionally scanned in a rest condition. KCC was compared among the three conditions (left finger movement, right finger movement, and the rest). Results show that bilateral primary motor cortex (M1) had higher KCC in either left or right finger movement condition than in rest condition. Contrary to prediction and to activation pattern, KCC of ipsilateral M1 is significantly higher than contralateral M1 in unilateral finger movement conditions. These results support the previous electrophysiologic findings of increasing ipsilateral M1 excitation during unilateral movement. ReHo can consider as a complementary method to model-driven method, and it could help reveal the complexity of the human brain function. More work is needed to understand the neural mechanism underlying ReHo.", month = "1~" # may, year = 2004, keywords = "RePhD;MRI Methods", doi = "10.1016/j.neuroimage.2003.12.030", language = "en" } @ARTICLE{Dennison2019-ix, title = "The human default consciousness and its disruption: Insights from an {EEG} study of Buddhist jhāna meditation", author = "Dennison, Paul", journal = "Front. Hum. Neurosci.", publisher = "Frontiers Media SA", volume = 13, pages = 178, abstract = "The ``neural correlates of consciousness'' (NCC) is a familiar topic in neuroscience, overlapping with research on the brain's ``default mode network.'' Task-based studies of NCC by their nature recruit one part of the cortical network to study another, and are therefore both limited and compromised in what they can reveal about consciousness itself. The form of consciousness explored in such research, we term the human default consciousness (DCs), our everyday waking consciousness. In contrast, studies of anesthesia, coma, deep sleep, or some extreme pathological states such as epilepsy, reveal very different cortical activity; all of which states are essentially involuntary, and generally regarded as ``unconscious.'' An exception to involuntary disruption of consciousness is Buddhist jhāna meditation, whose implicit aim is to intentionally withdraw from the default consciousness, to an inward-directed state of stillness referred to as jhāna consciousness, as a basis to develop insight. The default consciousness is sensorily-based, where information about, and our experience of, the outer world is evaluated against personal and organic needs and forms the basis of our ongoing self-experience. This view conforms both to Buddhist models, and to the emerging work on active inference and minimization of free energy in determining the network balance of the human default consciousness. This paper is a preliminary report on the first detailed EEG study of jhāna meditation, with findings radically different to studies of more familiar, less focused forms of meditation. While remaining highly alert and ``present'' in their subjective experience, a high proportion of subjects display ``spindle'' activity in their EEG, superficially similar to sleep spindles of stage 2 nREM sleep, while more-experienced subjects display high voltage slow-waves reminiscent, but significantly different, to the slow waves of deeper stage 4 nREM sleep, or even high-voltage delta coma. Some others show brief posterior spike-wave bursts, again similar, but with significant differences, to absence epilepsy. Some subjects also develop the ability to consciously evoke clonic seizure-like activity at will, under full control. We suggest that the remarkable nature of these observations reflects a profound disruption of the human DCs when the personal element is progressively withdrawn.", month = "12~" # jun, year = 2019, keywords = "EEG; active inference; consciousness; epilepsy; jhāna; meditation; slow-waves; spike-waves;RePhD;RePhD/unread;jhana;EEG;meditation", doi = "10.3389/fnhum.2019.00178", language = "en" } @ARTICLE{Zhang2023-ve, title = "Self-supervised time series representation learning via cross reconstruction transformer", author = "Zhang, Wenrui and Yang, Ling and Geng, Shijia and Hong, Shenda", journal = "IEEE Trans. Neural Netw. Learn. Syst.", publisher = "Institute of Electrical and Electronics Engineers (IEEE)", volume = "PP", number = 99, pages = "1--10", abstract = "Since labeled samples are typically scarce in real-world scenarios, self-supervised representation learning in time series is critical. Existing approaches mainly employ the contrastive learning framework, which automatically learns to understand similar and dissimilar data pairs. However, they are constrained by the request for cumbersome sampling policies and prior knowledge of constructing pairs. Also, few works have focused on effectively modeling temporal-spectral correlations to improve the capacity of representations. In this article, we propose the cross reconstruction transformer (CRT) to solve the aforementioned issues. CRT achieves time series representation learning through a cross-domain dropping-reconstruction task. Specifically, we obtain the frequency domain of the time series via the fast Fourier transform (FFT) and randomly drop certain patches in both time and frequency domains. Dropping is employed to maximally preserve the global context while masking leads to the distribution shift. Then a Transformer architecture is utilized to adequately discover the cross-domain correlations between temporal and spectral information through reconstructing data in both domains, which is called Dropped Temporal-Spectral Modeling. To discriminate the representations in global latent space, we propose instance discrimination constraint (IDC) to reduce the mutual information between different time series samples and sharpen the decision boundaries. Additionally, a specified curriculum learning (CL) strategy is employed to improve the robustness during the pretraining phase, which progressively increases the dropping ratio in the training process. We conduct extensive experiments to evaluate the effectiveness of the proposed method on multiple real-world datasets. Results show that CRT consistently achieves the best performance over existing methods by 2\%-9\%. The code is publicly available at https://github.com/BobZwr/Cross-Reconstruction-Transformer.", month = "21~" # jul, year = 2023, keywords = "RePhD;RePhD/unread;EEG;SSL", doi = "10.1109/TNNLS.2023.3292066", language = "en" } @ARTICLE{Weng2024-ez, title = "Self-supervised learning for electroencephalogram: A systematic survey", author = "Weng, Weining and Gu, Yang and Guo, Shuai and Ma, Yuan and Yang, Zhaohua and Liu, Yuchen and Chen, Yiqiang", journal = "arXiv [eess.SP]", abstract = "Electroencephalogram (EEG) is a non-invasive technique to record bioelectrical signals. Integrating supervised deep learning techniques with EEG signals has recently facilitated automatic analysis across diverse EEG-based tasks. However, the label issues of EEG signals have constrained the development of EEG-based deep models. Obtaining EEG annotations is difficult that requires domain experts to guide collection and labeling, and the variability of EEG signals among different subjects causes significant label shifts. To solve the above challenges, self-supervised learning (SSL) has been proposed to extract representations from unlabeled samples through well-designed pretext tasks. This paper concentrates on integrating SSL frameworks with temporal EEG signals to achieve efficient representation and proposes a systematic review of the SSL for EEG signals. In this paper, 1) we introduce the concept and theory of self-supervised learning and typical SSL frameworks. 2) We provide a comprehensive review of SSL for EEG analysis, including taxonomy, methodology, and technique details of the existing EEG-based SSL frameworks, and discuss the difference between these methods. 3) We investigate the adaptation of the SSL approach to various downstream tasks, including the task description and related benchmark datasets. 4) Finally, we discuss the potential directions for future SSL-EEG research.", month = "9~" # jan, year = 2024, archivePrefix = "arXiv", primaryClass = "eess.SP", keywords = "RePhD;RePhD/unread;EEG;Deep Learning" } @ARTICLE{Sparby2024-la, title = "Toward a unified account of advanced concentrative absorption meditation: A systematic definition and classification of jhāna", author = "Sparby, Terje and Sacchet, Matthew D", journal = "Mindfulness (N. Y.)", publisher = "Springer Science and Business Media LLC", volume = 15, number = 6, pages = "1375--1394", abstract = "Abstract Objectives The jhānas are series of advanced concentrative absorption meditative (ACAM) states brought about by meditation. While previously cultivated mostly in monastic settings, a series of modern meditation manuals both openly discuss the jhānas and describe how they may be attained by laypeople. Simultaneously, the phenomenological and neuroscientific investigation of the jhānas is advancing. Although the descriptions of the jhānas in contemporary jhāna manuals to some degree overlap with one another, there are also significant disagreements. Here our objectives are to identify common features of jhāna in meditation manuals, to identify and discuss disagreements, and to offer an account of jhāna that is both comprehensive and consistent. Methods A literature search and review was conducted. The search resulted in eight meditation manuals that provide phenomenologically rich accounts of the full range of the jhānas. Common characteristics and discrepancies in the different accounts of the jhānas have been identified by comparing terms and descriptions. Results We offer a general definition of jhāna, distinguish three types of jhāna, and investigate phenomenological dimensions that may be necessary to address in order to comprehensively articulate the experience of ACAM. Conclusions To ensure scientific rigor, the study of jhāna needs to be informed by both commonalities and differences in the existing accounts of jhāna. While differences exist, these may also be systematically unified in a way that yields a comprehensive account of ACAM.", month = "22~" # jun, year = 2024, keywords = "RePhD;RePhD/unread;fMRI Attention;meditation;jhana", doi = "10.1007/s12671-024-02367-w", language = "en" } @ARTICLE{Ganesan2024-ej, title = "Within-subject reliability of brain networks during advanced meditation: An intensively sampled 7 Tesla {MRI} case study", author = "Ganesan, Saampras and Yang, Winson F Z and Chowdhury, Avijit and Zalesky, Andrew and Sacchet, Matthew D", journal = "Hum. Brain Mapp.", publisher = "Wiley", volume = 45, number = 7, pages = "e26666", abstract = "Advanced meditation such as jhana meditation can produce various altered states of consciousness (jhanas) and cultivate rewarding psychological qualities including joy, peace, compassion, and attentional stability. Mapping the neurobiological substrates of jhana meditation can inform the development and application of advanced meditation to enhance well-being. Only two prior studies have attempted to investigate the neural correlates of jhana meditation, and the rarity of adept practitioners has largely restricted the size and extent of these studies. Therefore, examining the consistency and reliability of observed brain responses associated with jhana meditation can be valuable. In this study, we aimed to characterize functional magnetic resonance imaging (fMRI) reliability within a single subject over repeated runs in canonical brain networks during jhana meditation performed by an adept practitioner over 5 days (27 fMRI runs) inside an ultra-high field 7 Tesla MRI scanner. We found that thalamus and several cortical networks, that is, the somatomotor, limbic, default-mode, control, and temporo-parietal, demonstrated good within-subject reliability across all jhanas. Additionally, we found that several other relevant brain networks (e.g., attention, salience) showed noticeable increases in reliability when fMRI measurements were adjusted for variability in self-reported phenomenology related to jhana meditation. Overall, we present a preliminary template of reliable brain areas likely underpinning core neurocognitive elements of jhana meditation, and highlight the utility of neurophenomenological experimental designs for better characterizing neuronal variability associated with advanced meditative states.", month = "1~" # may, year = 2024, keywords = "7 T functional MRI; advanced meditation; consciousness; intraclass correlation (ICC); jhana; neurophenomenology; within-subject reliability;RePhD;RePhD/unread;fMRI Attention;jhana;meditation", doi = "10.1002/hbm.26666", language = "en" } @ARTICLE{Yang2024-kw, title = "Intensive whole-brain {7T} {MRI} case study of volitional control of brain activity in deep absorptive meditation states", author = "Yang, Winson Fu Zun and Chowdhury, Avijit and Bianciardi, Marta and van Lutterveld, Remko and Sparby, Terje and Sacchet, Matthew D", journal = "Cereb. Cortex", publisher = "Oxford University Press (OUP)", volume = 34, number = 1, pages = "bhad408", abstract = "Jhanas are profound states of mind achieved through advanced meditation, offering valuable insights into the nature of consciousness and tools to enhance well-being. Yet, its neurophenomenology remains limited due to methodological difficulties and the rarity of advanced meditation practitioners. We conducted a highly exploratory study to investigate the neurophenomenology of jhanas in an intensively sampled adept meditator case study (4 hr 7T fMRI collected in 27 sessions) who performed jhana meditation and rated specific aspects of experience immediately thereafter. Linear mixed models and correlations were used to examine relations among brain activity and jhana phenomenology. We identified distinctive patterns of brain activity in specific cortical, subcortical, brainstem, and cerebellar regions associated with jhana. Furthermore, we observed correlations between brain activity and phenomenological qualities of attention, jhanic qualities, and narrative processing, highlighting the distinct nature of jhanas compared to non-meditative states. Our study presents the most rigorous evidence yet that jhana practice deconstructs consciousness, offering unique insights into consciousness and significant implications for mental health and well-being.", month = "14~" # jan, year = 2024, keywords = "7T functional magnetic resonance imaging (fMRI); advanced meditation; brainstem and thalamus; consciousness; neurophenomenology;RePhD;RePhD/unread;fMRI Attention;jhana;meditation", doi = "10.1093/cercor/bhad408", language = "en" } @ARTICLE{Yeo2011-kp, title = "The organization of the human cerebral cortex estimated by intrinsic functional connectivity", author = "Yeo, B T Thomas and Krienen, Fenna M and Sepulcre, Jorge and Sabuncu, Mert R and Lashkari, Danial and Hollinshead, Marisa and Roffman, Joshua L and Smoller, Jordan W and Zöllei, Lilla and Polimeni, Jonathan R and Fischl, Bruce and Liu, Hesheng and Buckner, Randy L", journal = "J. Neurophysiol.", publisher = "American Physiological Society", volume = 106, number = 3, pages = "1125--1165", abstract = "Information processing in the cerebral cortex involves interactions among distributed areas. Anatomical connectivity suggests that certain areas form local hierarchical relations such as within the visual system. Other connectivity patterns, particularly among association areas, suggest the presence of large-scale circuits without clear hierarchical relations. In this study the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI. Data from 1,000 subjects were registered using surface-based alignment. A clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex. The results revealed local networks confined to sensory and motor cortices as well as distributed networks of association regions. Within the sensory and motor cortices, functional connectivity followed topographic representations across adjacent areas. In association cortex, the connectivity patterns often showed abrupt transitions between network boundaries. Focused analyses were performed to better understand properties of network connectivity. A canonical sensory-motor pathway involving primary visual area, putative middle temporal area complex (MT+), lateral intraparietal area, and frontal eye field was analyzed to explore how interactions might arise within and between networks. Results showed that adjacent regions of the MT+ complex demonstrate differential connectivity consistent with a hierarchical pathway that spans networks. The functional connectivity of parietal and prefrontal association cortices was next explored. Distinct connectivity profiles of neighboring regions suggest they participate in distributed networks that, while showing evidence for interactions, are embedded within largely parallel, interdigitated circuits. We conclude by discussing the organization of these large-scale cerebral networks in relation to monkey anatomy and their potential evolutionary expansion in humans to support cognition.", month = sep, year = 2011, keywords = "RePhD;RePhD/unread", doi = "10.1152/jn.00338.2011", language = "en" } @ARTICLE{Zhang2021-gm, title = "Longitudinal effects of meditation on brain resting-state functional connectivity", author = "Zhang, Zongpai and Luh, Wen-Ming and Duan, Wenna and Zhou, Grace D and Weinschenk, George and Anderson, Adam K and Dai, Weiying", journal = "Sci. Rep.", publisher = "Springer Science and Business Media LLC", volume = 11, number = 1, pages = 11361, abstract = "Changes in brain resting-state functional connectivity (rsFC) were investigated using a longitudinal design by following a 2-month focused attention meditation (FAM) practice and analyzing their association with FAM practice time. Ten novice meditators were recruited from a university meditation course. Participants were scanned with a resting-state fMRI sequence with multi-echo EPI acquisition at baseline and at the 2-month follow-up. Total FAM practice time was calculated from the daily log of the participants. We observed significantly increased rsFC between the posterior cingulate cortex (PCC) and dorsal attention network (DAN), the right middle temporal (RMT) region and default mode network (DMN), the left and right superior parietal lobules (LSPL/RSPL) and DMN, and the LSPL/RSPL and DAN. Furthermore, the rsFC between the LSPL and medial prefrontal cortex was significantly associated with the FAM practice time. These results demonstrate increased connectivity within the DAN, between the DMN and DAN, and between the DMN and visual cortex. These findings demonstrate that FAM can enhance the brain connection among and within brain networks, especially DMN and DAN, indicating potential effect of FAM on fast switching between mind wandering and focused attention and maintaining attention once in the attentive state.", month = "31~" # may, year = 2021, keywords = "RePhD;RePhD/unread;meditation", doi = "10.1038/s41598-021-90729-y", language = "en" } @ARTICLE{Garrison2015-gi, title = "Meditation leads to reduced default mode network activity beyond an active task", author = "Garrison, Kathleen A and Zeffiro, Thomas A and Scheinost, Dustin and Constable, R Todd and Brewer, Judson A", journal = "Cogn. Affect. Behav. Neurosci.", volume = 15, number = 3, pages = "712--720", abstract = "Meditation has been associated with relatively reduced activity in the default mode network, a brain network implicated in self-related thinking and mind wandering. However, previous imaging studies have typically compared meditation to rest, despite other studies having reported differences in brain activation patterns between meditators and controls at rest. Moreover, rest is associated with a range of brain activation patterns across individuals that has only recently begun to be better characterized. Therefore, in this study we compared meditation to another active cognitive task, both to replicate the findings that meditation is associated with relatively reduced default mode network activity and to extend these findings by testing whether default mode activity was reduced during meditation, beyond the typical reductions observed during effortful tasks. In addition, prior studies had used small groups, whereas in the present study we tested these hypotheses in a larger group. The results indicated that meditation is associated with reduced activations in the default mode network, relative to an active task, for meditators as compared to controls. Regions of the default mode network showing a Group × Task interaction included the posterior cingulate/precuneus and anterior cingulate cortex. These findings replicate and extend prior work indicating that the suppression of default mode processing may represent a central neural process in long-term meditation, and they suggest that meditation leads to relatively reduced default mode processing beyond that observed during another active cognitive task.", month = sep, year = 2015, keywords = "RePhD;RePhD/unread;meditation;DMN", doi = "10.3758/s13415-015-0358-3", language = "en" } @ARTICLE{Lutz2015-xi, title = "Investigating the phenomenological matrix of mindfulness-related practices from a neurocognitive perspective", author = "Lutz, Antoine and Jha, Amishi P and Dunne, John D and Saron, Clifford D", journal = "Am. Psychol.", publisher = "American Psychological Association (APA)", volume = 70, number = 7, pages = "632--658", abstract = "There has been a great increase in literature concerned with the effects of a variety of mental training regimes that generally fall within what might be called contemplative practices, and a majority of these studies have focused on mindfulness. Mindfulness meditation practices can be conceptualized as a set of attention-based, regulatory, and self-inquiry training regimes cultivated for various ends, including wellbeing and psychological health. This article examines the construct of mindfulness in psychological research and reviews recent, nonclinical work in this area. Instead of proposing a single definition of mindfulness, we interpret it as a continuum of practices involving states and processes that can be mapped into a multidimensional phenomenological matrix which itself can be expressed in a neurocognitive framework. This phenomenological matrix of mindfulness is presented as a heuristic to guide formulation of next-generation research hypotheses from both cognitive/behavioral and neuroscientific perspectives. In relation to this framework, we review selected findings on mindfulness cultivated through practices in traditional and research settings, and we conclude by identifying significant gaps in the literature and outline new directions for research.", month = oct, year = 2015, keywords = "RePhD;RePhD/unread;meditation", doi = "10.1037/a0039585", language = "en" } @ARTICLE{Lutz2008-ni, title = "Attention regulation and monitoring in meditation", author = "Lutz, Antoine and Slagter, Heleen A and Dunne, John D and Davidson, Richard J", journal = "Trends Cogn. Sci.", publisher = "Elsevier BV", volume = 12, number = 4, pages = "163--169", abstract = "Meditation can be conceptualized as a family of complex emotional and attentional regulatory training regimes developed for various ends, including the cultivation of well-being and emotional balance. Among these various practices, there are two styles that are commonly studied. One style, focused attention meditation, entails the voluntary focusing of attention on a chosen object. The other style, open monitoring meditation, involves nonreactive monitoring of the content of experience from moment to moment. The potential regulatory functions of these practices on attention and emotion processes could have a long-term impact on the brain and behavior.", month = apr, year = 2008, keywords = "RePhD;RePhD/unread;meditation;attention", doi = "10.1016/j.tics.2008.01.005", language = "en" } @ARTICLE{Tang2015-tw, title = "The neuroscience of mindfulness meditation", author = "Tang, Yi-Yuan and Hölzel, Britta K and Posner, Michael I", journal = "Nat. Rev. Neurosci.", publisher = "Springer Science and Business Media LLC", volume = 16, number = 4, pages = "213--225", abstract = "Research over the past two decades broadly supports the claim that mindfulness meditation - practiced widely for the reduction of stress and promotion of health - exerts beneficial effects on physical and mental health, and cognitive performance. Recent neuroimaging studies have begun to uncover the brain areas and networks that mediate these positive effects. However, the underlying neural mechanisms remain unclear, and it is apparent that more methodologically rigorous studies are required if we are to gain a full understanding of the neuronal and molecular bases of the changes in the brain that accompany mindfulness meditation.", month = apr, year = 2015, keywords = "RePhD;RePhD/unread;meditation", doi = "10.1038/nrn3916", language = "en" } @ARTICLE{Brewer2011-le, title = "Meditation experience is associated with differences in default mode network activity and connectivity", author = "Brewer, Judson A and Worhunsky, Patrick D and Gray, Jeremy R and Tang, Yi-Yuan and Weber, Jochen and Kober, Hedy", journal = "Proc. Natl. Acad. Sci. U. S. A.", publisher = "Proceedings of the National Academy of Sciences", volume = 108, number = 50, pages = "20254--20259", abstract = "Many philosophical and contemplative traditions teach that ``living in the moment'' increases happiness. However, the default mode of humans appears to be that of mind-wandering, which correlates with unhappiness, and with activation in a network of brain areas associated with self-referential processing. We investigated brain activity in experienced meditators and matched meditation-naive controls as they performed several different meditations (Concentration, Loving-Kindness, Choiceless Awareness). We found that the main nodes of the default-mode network (medial prefrontal and posterior cingulate cortices) were relatively deactivated in experienced meditators across all meditation types. Furthermore, functional connectivity analysis revealed stronger coupling in experienced meditators between the posterior cingulate, dorsal anterior cingulate, and dorsolateral prefrontal cortices (regions previously implicated in self-monitoring and cognitive control), both at baseline and during meditation. Our findings demonstrate differences in the default-mode network that are consistent with decreased mind-wandering. As such, these provide a unique understanding of possible neural mechanisms of meditation.", month = "13~" # dec, year = 2011, keywords = "2024-08-5-hedy-kober;RePhD;RePhD/unread;meditation", doi = "10.1073/pnas.1112029108", language = "en" } @ARTICLE{Hagerty2013-en, title = "Case Study of Ecstatic Meditation: {fMRI} and {EEG} Evidence of Self-Stimulating a Reward System", author = "Hagerty, M and Isaacs, J and Brasington, Leigh and Shupe, L and Fetz, E and Cramer, S", journal = "Neural Plast.", volume = 2013, pages = "null", abstract = "We report the first neural recording during ecstatic meditations called jhanas and test whether a brain reward system plays a role in the joy reported. Jhanas are Altered States of Consciousness (ASC) that imply major brain changes based on subjective reports: (1) external awareness dims, (2) internal verbalizations fade, (3) the sense of personal boundaries is altered, (4) attention is highly focused on the object of meditation, and (5) joy increases to high levels. The fMRI and EEG results from an experienced meditator show changes in brain activity in 11 regions shown to be associated with the subjective reports, and these changes occur promptly after jhana is entered. In particular, the extreme joy is associated not only with activation of cortical processes but also with activation of the nucleus accumbens (NAc) in the dopamine/opioid reward system. We test three mechanisms by which the subject might stimulate his own reward system by external means and reject all three. Taken together, these results demonstrate an apparently novel method of self-stimulating a brain reward system using only internal mental processes in a highly trained subject.", year = 2013, keywords = "2024-08-5-jhana-graph;RePhD;RePhD/unread;meditation;jhana", doi = "10.1155/2013/653572" } @ARTICLE{Hinterberger2014-kc, title = "Decreased electrophysiological activity represents the conscious state of emptiness in meditation", author = "Hinterberger, T and Schmidt, S and Kamei, T and Walach, H", journal = "Front. Psychol.", volume = 5, pages = "null", abstract = "Many neuroscientific theories explain consciousness with higher order information processing corresponding to an activation of specific brain areas and processes. In contrast, most forms of meditation ask for a down-regulation of certain mental processing activities while remaining fully conscious. To identify the physiological properties of conscious states with decreased mental and cognitive processing, the electrical brain activity (64 channels of EEG) of 50 participants of various meditation proficiencies was measured during distinct and idiosyncratic meditative tasks. The tasks comprised a wakeful “thoughtless emptiness (TE),” a “focused attention,” and an “open monitoring” task asking for mindful presence in the moment and in the environment without attachment to distracting thoughts. Our analysis mainly focused on 30 highly experienced meditators with at least 5 years and 1000 h of meditation experience. Spectral EEG power comparisons of the TE state with the resting state or other forms of meditation showed decreased activities in specific frequency bands. In contrast to a focused attention task the TE task showed significant central and parietal gamma decreases (p < 0.05). Compared to open monitoring TE expressed decreased alpha and beta amplitudes, mainly in parietal areas (p < 0.01). TE presented significantly less delta (p < 0.001) and theta (p < 0.05) waves than a wakeful closed eyes resting condition. A group of participants with none or little meditation practice did not present those differences significantly. Our findings indicate that a conscious state of TE reached by experienced meditators is characterized by reduced high-frequency brain processing with simultaneous reduction of the low frequencies. This suggests that such a state of meditative conscious awareness might be different from higher cognitive and mentally focused states but also from states of sleep and drowsiness.", year = 2014, keywords = "2024-08-5-jhana-graph;RePhD;RePhD/unread;meditation", doi = "10.3389/fpsyg.2014.00099" } @ARTICLE{Galante2023-an, title = "A Framework for the Empirical Investigation of Mindfulness Meditative Development", author = "Galante, J and Grabovac, A and Wright, Malcolm J and Ingram, Daniel M and Van Dam, N V and Sanguinetti, Joseph L and Sparby, T and van Lutterveld, R and Sacchet, M", journal = "Mindfulness (N. Y.)", pages = "1--14", abstract = "Millions of people globally have learned mindfulness meditation with the goal of improving health and well-being outcomes in both clinical and non-clinical contexts. An estimated half of these practitioners follow mindfulness teachers’ recommendations to continue regular meditation after completion of initial instruction, but it is unclear whether benefits are strengthened by regular practice and whether harm can occur. Increasing evidence shows a wide range of experiences that can arise with regular mindfulness meditation, from profoundly positive to challenging and potentially harmful. Initial research suggests that complex interactions and temporal sequences may explain these experiential phenomena and their relations to health and well-being. We believe further study of the effects of mindfulness meditation is urgently needed to better understand the benefits and challenges of continued practice after initial instructions. Effects may vary systematically over time due to factors such as initial dosage, accumulation of ongoing practice, developing skill of the meditator, and complex interactions with the subjects’ past experiences and present environment. We propose that framing mindfulness meditation experiences and any associated health and well-being benefits within integrated longitudinal models may be more illuminating than treating them as discrete, unrelated events. We call for ontologically agnostic, collaborative, and interdisciplinary research to study the effects of continued mindfulness meditation and their contexts, advancing the view that practical information found within religious and spiritual contemplative traditions can serve to develop initial theories and scientifically falsifiable hypotheses. Such investigation could inform safer and more effective applications of mindfulness meditation training for improving health and well-being.", year = 2023, keywords = "2024-08-5-jhana-graph;RePhD;RePhD/read;meditation;read", doi = "10.1007/s12671-023-02113-8" } @ARTICLE{Tang2009-uz, title = "Central and autonomic nervous system interaction is altered by short-term meditation", author = "Tang, Yi-Yuan and Ma, Yinghua and Fan, Yaxin and Feng, Hongbo and Wang, Junhong and Feng, Shigang and Lu, Q and Hu, B and Lin, Yao and Li, Jian and Zhang, Ye and Wang, Yan and Zhou, Li and Fan, M", journal = "Proc. Natl. Acad. Sci. U. S. A.", volume = 106, pages = "8865--8870", abstract = "Five days of integrative body–mind training (IBMT) improves attention and self-regulation in comparison with the same amount of relaxation training. This paper explores the underlying mechanisms of this finding. We measured the physiological and brain changes at rest before, during, and after 5 days of IBMT and relaxation training. During and after training, the IBMT group showed significantly better physiological reactions in heart rate, respiratory amplitude and rate, and skin conductance response (SCR) than the relaxation control. Differences in heart rate variability (HRV) and EEG power suggested greater involvement of the autonomic nervous system (ANS) in the IBMT group during and after training. Imaging data demonstrated stronger subgenual and adjacent ventral anterior cingulate cortex (ACC) activity in the IBMT group. Frontal midline ACC theta was correlated with highfrequency HRV, suggesting control by the ACC over parasympathetic activity. These results indicate that after 5 days of training, the IBMT group shows better regulation of the ANS by a ventral midfrontal brain system than does the relaxation group. This changed state probably reflects training in the coordination of body and mind given in the IBMT but not in the control group. These results could be useful in the design of further specific interventions.", year = 2009, keywords = "2024-08-5-jhana-graph;RePhD;RePhD/unread;meditation", doi = "10.1073/pnas.0904031106" } @ARTICLE{Nash2013-of, title = "Toward a unifying taxonomy and definition for meditation", author = "Nash, Jonathan and Newberg, A and Awasthi, Bhuvanesh", journal = "Front. Psychol.", volume = 4, pages = "null", abstract = "One of the well-documented concerns confronting scholarly discourse about meditation is the plethora of semantic constructs and the lack of a unified definition and taxonomy. In recent years there have been several notable attempts to formulate new lexicons in order to define and categorize meditation methods. While these constructs have been useful and have encountered varying degrees of acceptance, they have also been subject to misinterpretation and debate, leaving the field devoid of a consensual paradigm. This paper attempts to influence this ongoing discussion by proposing two new models which hold the potential for enhanced scientific reliability and acceptance. Regarding the quest for a universally acceptable taxonomy, we suggest a paradigm shift away from the norm of fabricatIng new terminology from a first-person perspective. As an alternative, we propose a new taxonomic system based on the historically well-established and commonly accepted third-person paradigm of Affect and Cognition, borrowed, in part, from the psychological and cognitive sciences. With regard to the elusive definitional problem, we propose a model of meditation which clearly distinguishes “method” from “state” and is conceptualized as a dynamic process which is inclusive of six related but distinct stages. The overall goal is to provide researchers with a reliable nomenclature with which to categorize and classify diverse meditation methods, and a conceptual framework which can provide direction for their research and a theoretical basis for their findings.", year = 2013, keywords = "2024-08-5-jhana-graph;RePhD;RePhD/unread;meditation", doi = "10.3389/fpsyg.2013.00806" } @ARTICLE{Josipovic2012-fv, title = "Influence of meditation on anti-correlated networks in the brain", author = "Josipovic, Zoran and Dinstein, I and Weber, J and Heeger, D", journal = "Front. Hum. Neurosci.", volume = 5, pages = "null", abstract = "Human experiences can be broadly divided into those that are external and related to interaction with the environment, and experiences that are internal and self-related. The cerebral cortex appears to be divided into two corresponding systems: an “extrinsic” system composed of brain areas that respond more to external stimuli and tasks and an “intrinsic” system composed of brain areas that respond less to external stimuli and tasks. These two broad brain systems seem to compete with each other, such that their activity levels over time is usually anti-correlated, even when subjects are “at rest” and not performing any task. This study used meditation as an experimental manipulation to test whether this competition (anti-correlation) can be modulated by cognitive strategy. Participants either fixated without meditation (fixation), or engaged in non-dual awareness (NDA) or focused attention (FA) meditations. We computed inter-area correlations (“functional connectivity”) between pairs of brain regions within each system, and between the entire extrinsic and intrinsic systems. Anti-correlation between extrinsic vs. intrinsic systems was stronger during FA meditation and weaker during NDA meditation in comparison to fixation (without mediation). However, correlation between areas within each system did not change across conditions. These results suggest that the anti-correlation found between extrinsic and intrinsic systems is not an immutable property of brain organization and that practicing different forms of meditation can modulate this gross functional organization in profoundly different ways.", year = 2012, keywords = "2024-08-5-jhana-graph;RePhD;RePhD/unread;meditation", doi = "10.3389/fnhum.2011.00183" } @ARTICLE{Lehmann2012-pn, title = "Reduced functional connectivity between cortical sources in five meditation traditions detected with lagged coherence using {EEG} tomography", author = "Lehmann, D and Faber, P and Tei, S and Pascual-Marqui, R and Milz, P and Kochi, K", journal = "NeuroImage", volume = 60, pages = "1574--1586", abstract = "Brain functional states are established by functional connectivities between brain regions. In experienced meditators (13 Tibetan Buddhists, 15 QiGong, 14 Sahaja Yoga, 14 Ananda Marga Yoga, 15 Zen), 19-channel EEG was recorded before, during and after that meditation exercise which their respective tradition regards as route to the most desirable meditative state. The head surface EEG data were recomputed (sLORETA) into 19 cortical regional source model time series. All 171 functional connectivities between regions were computed as ‘lagged coherence’ for the eight EEG frequency bands (delta through gamma). This analysis removes ambiguities of localization, volume conduction-induced inflation of coherence, and reference-dependence. All significant differences (corrected for multiple testing) between meditation compared to no-task rest before and after meditation showed lower coherence during meditation, in all five traditions and eight (inhibitory as well as excitatory) frequency bands. Conventional coherence between the original head surface EEG time series very predominantly also showed reduced coherence during meditation. The topography of the functional connectivities was examined via PCA-based computation of principal connectivities. When going into and out of meditation, significantly different connectivities revealed clearly different topographies in the delta frequency band and minor differences in the beta-2 band. The globally reduced functional interdependence between brain regions in meditation suggests that interaction between the self process functions is minimized, and that constraints on the self process by other processes are minimized, thereby leading to the subjective experience of non-involvement, detachment and letting go, as well as of all-oneness and dissolution of ego borders during meditation.", year = 2012, keywords = "2024-08-5-jhana-graph;RePhD;RePhD/unread;meditation", doi = "10.1016/j.neuroimage.2012.01.042" } @ARTICLE{Hernandez2015-tt, title = "Monitoring the neural activity of the state of mental silence while practicing Sahaja yoga meditation", author = "Hernández, S and Suero, José and Rubia, K and González-Mora, J", journal = "Journal of alternative and complementary medicine", volume = "21 3", pages = "175--179", abstract = "Objective: To identify the neural correlates of the state of mental silence as experienced through Sahaja yoga meditation. Design: Nineteen experienced meditators underwent functional magnetic resonance imaging during three short consecutive meditation periods, contrasted with a control relaxation condition. Results: Relative to baseline, at the beginning of the meditation sessions there was a significant increase of activation in bilateral inferior frontal and temporal regions. Activation became progressively more reduced with deeper meditation stages and in the last meditation session it became localized to the right inferior frontal cortex/ right insula and right middle/superior temporal cortex. Furthermore, right inferior frontal activation was directly associated with the subjective depth of the mental silence experience. Conclusions: Meditators appear to pass through an initial intense neural self-control process necessary to silence their mind. After this they experience relatively reduced brain activation concomitant with the deepening of the state of mental silence over right inferior frontal cortex, probably reflecting an effortless process of attentional contemplation associated with this state.", year = 2015, keywords = "2024-08-5-jhana-graph;RePhD;RePhD/unread;meditation", doi = "10.1089/acm.2013.0450" } @ARTICLE{Milliere2018-mq, title = "Psychedelics, Meditation, and Self-Consciousness", author = "Millière, Raphaël and Carhart-Harris, R and Roseman, L and Trautwein, Fynn-Mathis and Berkovich-Ohana, Aviva", journal = "Front. Psychol.", volume = 9, pages = "null", abstract = "In recent years, the scientific study of meditation and psychedelic drugs has seen remarkable developments. The increased focus on meditation in cognitive neuroscience has led to a cross-cultural classification of standard meditation styles validated by functional and structural neuroanatomical data. Meanwhile, the renaissance of psychedelic research has shed light on the neurophysiology of altered states of consciousness induced by classical psychedelics, such as psilocybin and LSD, whose effects are mainly mediated by agonism of serotonin receptors. Few attempts have been made at bridging these two domains of inquiry, despite intriguing evidence of overlap between the phenomenology and neurophysiology of meditation practice and psychedelic states. In particular, many contemplative traditions explicitly aim at dissolving the sense of self by eliciting altered states of consciousness through meditation, while classical psychedelics are known to produce significant disruptions of self-consciousness, a phenomenon known as drug-induced ego dissolution. In this article, we discuss available evidence regarding convergences and differences between phenomenological and neurophysiological data on meditation practice and psychedelic drug-induced states, with a particular emphasis on alterations of self-experience. While both meditation and psychedelics may disrupt self-consciousness and underlying neural processes, we emphasize that neither meditation nor psychedelic states can be conceived as simple, uniform categories. Moreover, we suggest that there are important phenomenological differences even between conscious states described as experiences of self-loss. As a result, we propose that self-consciousness may be best construed as a multidimensional construct, and that ``self-loss,'' far from being an unequivocal phenomenon, can take several forms. Indeed, various aspects of self-consciousness, including narrative aspects linked to autobiographical memory, self-related thoughts and mental time travel, and embodied aspects rooted in multisensory processes, may be differently affected by psychedelics and meditation practices. Finally, we consider long-term outcomes of experiences of self-loss induced by meditation and psychedelics on individual traits and prosocial behavior. We call for caution regarding the problematic conflation of temporary states of self-loss with ``selflessness'' as a behavioral or social trait, although there is preliminary evidence that correlations between short-term experiences of self-loss and long-term trait alterations may exist.", year = 2018, keywords = "2024-08-5-saved-papers;RePhD;RePhD/unread;psychedelics;meditation", doi = "10.3389/fpsyg.2018.01475" } @ARTICLE{Carhart-Harris2019-ek, title = "{REBUS} and the Anarchic Brain: Toward a Unified Model of the Brain Action of Psychedelics", author = "Carhart-Harris, R and Friston, Karl J", journal = "Pharmacol. Rev.", volume = 71, pages = "316--344", abstract = "This paper formulates the action of psychedelics by integrating the free-energy principle and entropic brain hypothesis. We call this formulation relaxed beliefs under psychedelics (REBUS) and the anarchic brain, founded on the principle that—via their entropic effect on spontaneous cortical activity—psychedelics work to relax the precision of high-level priors or beliefs, thereby liberating bottom-up information flow, particularly via intrinsic sources such as the limbic system. We assemble evidence for this model and show how it can explain a broad range of phenomena associated with the psychedelic experience. With regard to their potential therapeutic use, we propose that psychedelics work to relax the precision weighting of pathologically overweighted priors underpinning various expressions of mental illness. We propose that this process entails an increased sensitization of high-level priors to bottom-up signaling (stemming from intrinsic sources), and that this heightened sensitivity enables the potential revision and deweighting of overweighted priors. We end by discussing further implications of the model, such as that psychedelics can bring about the revision of other heavily weighted high-level priors, not directly related to mental health, such as those underlying partisan and/or overly-confident political, religious, and/or philosophical perspectives.", year = 2019, keywords = "2024-08-5-saved-papers;RePhD;RePhD/unread;psychedelics", doi = "10.1124/pr.118.017160" } @ARTICLE{Dor-Ziderman2016-pg, title = "Self-specific processing in the meditating brain: a {MEG} neurophenomenology study", author = "Dor-Ziderman, Yair and Ataria, Y and Fulder, S and Goldstein, A and Berkovich-Ohana, Aviva", journal = "Neurosci. Conscious.", volume = 2016, pages = "null", abstract = "Self-specific processes (SSPs) specify the self as an embodied subject and agent, implementing a functional self/nonself distinction in perception, cognition, and action. Despite recent interest, it is still undetermined whether SSPs are all-or-nothing or graded phenomena; whether they can be identified in neuroimaging data; and whether they can be altered through attentional training. These issues are approached through a neurophenomenological exploration of the sense-of-boundaries (SB), the fundamental experience of being an ‘I’ (self) separated from the ‘world' (nonself). The SB experience was explored in collaboration with a uniquely qualified meditation practitioner, who volitionally produced, while being scanned by magnetoencephalogram (MEG), three mental states characterized by a graded SB experience. The results were then partly validated in an independent group of 10 long-term meditators. Implicated neural mechanisms include right-lateralized beta oscillations in the temporo-parietal junction, a region known to mediate the experiential unity of self and body; and in the medial parietal cortex, a central node of the self's representational system. The graded nature as well as the trainable flexibility and neural plasticity of SSPs may hold clinical implications for populations with a disturbed SB.", year = 2016, keywords = "2024-08-5-saved-papers;RePhD;RePhD/unread;meditation", doi = "10.1093/nc/niw019" } @ARTICLE{Metzingera2020-ry, title = "Minimal phenomenal experience: Meditation, tonic alertness, and the phenomenology of ``pure'' consciousness", author = "Metzingera, Thomas and Metzinger, T", abstract = "This is the first in a series of instalments aiming at a minimal model explanation for conscious experience, taking the phenomenal character of “pure consciousness” or “pure awareness” in meditation as its entry point. It develops the concept of “minimal phenomenal experience” (MPE) as a candidate for the simplest form of consciousness, substantiating it by extracting six semantic constraints from the existing literature and using sixteen phenomenological case-studies to incrementally flesh out the new working concept. One empirical hypothesis is that the phenomenological prototype of “pure awareness”, to which all such reports refer, really is the content of a predictive model, namely, a Bayesian representation of tonic alertness. On a more abstract conceptual level, it can be described as a model of an unpartitioned epistemic space", year = 2020, keywords = "2024-08-5-saved-papers;RePhD;RePhD/unread;meditation" } @ARTICLE{Tripathi2024-gp, title = "Silence Practice Modulates the Resting State Functional Connectivity of Language Network with Default Mode and Dorsal Attention Networks in Long-Term Meditators", author = "Tripathi, Vaibhav and Devaney, Kathryn J and Lazar, Sara W and Somers, David C", journal = "Mindfulness (N. Y.)", volume = "null", pages = "null", year = 2024, keywords = "2024-08-5-saved-papers;RePhD;RePhD/unread;meditation", doi = "10.1007/s12671-024-02316-7" } @ARTICLE{Buckner2019-sh, title = "The brain’s default network: updated anatomy, physiology and evolving insights", author = "Buckner, R and DiNicola, L", journal = "Nat. Rev. Neurosci.", volume = 20, pages = "593--608", abstract = "Discoveries over the past two decades demonstrate that regions distributed throughout the association cortex, often called the default network, are suppressed during tasks that demand external attention and are active during remembering, envisioning the future and making social inferences. This Review describes progress in understanding the organization and function of networks embedded within these association regions. Detailed high-resolution analyses of single individuals suggest that the default network is not a single network, as historically described, but instead comprises multiple interwoven networks. The multiple networks share a common organizational motif (also evident in marmoset and macaque anatomical circuits) that might support a general class of processing function dependent on internally constructed rather than externally constrained representations, with each separate interwoven network specialized for a distinct processing domain. Direct neuronal recordings in humans and monkeys reveal evidence for competitive relationships between the internally and externally oriented networks. Findings from rodent studies suggest that the thalamus might be essential to controlling which networks are engaged through specialized thalamic reticular neurons, including antagonistic subpopulations. These association networks (and presumably thalamocortical circuits) are expanded in humans and might be particularly vulnerable to dysregulation implicated in mental illness.", year = 2019, keywords = "2024-08-5-saved-papers;RePhD;RePhD/unread;MRI Methods", doi = "10.1038/s41583-019-0212-7" } @ARTICLE{Devaney2019-lz, title = "Identification of Visual Attentional Regions of the Temporoparietal Junction in Individual Subjects using a Vivid, Novel Oddball Paradigm", author = "Devaney, Kathryn J and Rosen, M and Levin, Emily J and Somers, D", journal = "Front. Hum. Neurosci.", volume = 13, pages = "null", abstract = "The Temporoparietal Junction (TPJ) of the cerebral cortex is a functionally heterogeneous region that also exhibits substantial anatomical variability across individuals. As a result, the precise functional organization of TPJ remains controversial. One or more regions within TPJ support visual attention processes, but the “attention TPJ” is difficult to functionally observe in individual subjects, and thus is typically identified by averaging across a large group of subjects. However, group-averaging also blurs localization and can obscure functional organization. Here, we develop and test an individual-subject approach to identifying attentional TPJ. This paradigm employs novel oddball images with a strong visual drive to produce robust TPJ responses in individuals. Vivid, novel oddballs drive responses in two TPJ regions bilaterally, a posterior region centered in posterior Superior Temporal Sulcus (TPJSTS) and an anterior region in ventral Supramarginal Gyrus (TPJSMG). Although an attentional reorienting task fails to drive TPJ activation in individuals, group analysis of the attentional reorienting contrast reveals recruitment of right TPJSTS, but not right TPJSMG. Similarly, right TPJSTS, as identified in individual subjects by the vivid, novel oddball contrast, is activated by attentional reorienting, but right TPJSMG is not. These findings advance an individual-subject based approach to understanding the functional organization of TPJ.", year = 2019, keywords = "2024-08-5-saved-papers;RePhD;RePhD/unread;meditation", doi = "10.3389/fnhum.2019.00424" } @ARTICLE{Fialoke2024-zk, title = "Functional connectivity changes in meditators and novices during yoga nidra practice", author = "Fialoke, Suruchi and Tripathi, Vaibhav and Thakral, Sonika and Dhawan, Anju and Majahan, Vidur and Garg, Rahul", journal = "Scientific Reports", volume = 14, pages = "null", abstract = "Yoga nidra (YN) practice aims to induce a deeply relaxed state akin to sleep while maintaining heightened awareness. Despite the growing interest in its clinical applications, a comprehensive understanding of the underlying neural correlates of the practice of YN remains largely unexplored. In this fMRI investigation, we aim to discover the differences between wakeful resting states and states attained during YN practice. The study included individuals experienced in meditation and/or yogic practices, referred to as ‘meditators’ (n = 30), and novice controls (n = 31). The GLM analysis, based on audio instructions, demonstrated activation related to auditory cues without concurrent default mode network (DMN) deactivation. DMN seed based functional connectivity (FC) analysis revealed significant reductions in connectivity among meditators during YN as compared to controls. We did not find differences between the two groups during the pre and post resting state scans. Moreover, when DMN-FC was compared between the YN state and resting state, meditators showed distinct decoupling, whereas controls showed increased DMN-FC. Finally, participants exhibit a remarkable correlation between reduced DMN connectivity during YN and self-reported hours of cumulative meditation and yoga practice. Together, these results suggest a unique neural modulation of the DMN in meditators during YN which results in being restful yet aware, aligned with their subjective experience of the practice. The study deepens our understanding of the neural mechanisms of YN, revealing distinct DMN connectivity decoupling in meditators and its relationship with meditation and yoga experience. These findings have interdisciplinary implications for neuroscience, psychology, and yogic disciplines.", year = 2024, keywords = "2024-08-5-saved-papers;RePhD;RePhD/unread;meditation", doi = "10.1038/s41598-024-63765-7" } @ARTICLE{Mooneyham2016-uo, title = "Signal or noise: brain network interactions underlying the experience and training of mindfulness", author = "Mooneyham, Benjamin W and Mrazek, M and Mrazek, Alissa J and Schooler, J", journal = "Ann. N. Y. Acad. Sci.", volume = 1369, pages = "null", abstract = "A broad set of brain regions has been associated with the experience and training of mindfulness. Many of these regions lie within key intrinsic brain networks, including the executive control, salience, and default networks. In this paper, we review the existing literature on the cognitive neuroscience of mindfulness through the lens of network science. We describe the characteristics of the intrinsic brain networks implicated in mindfulness and summarize the relevant findings pertaining to changes in functional connectivity (FC) within and between these networks. Convergence across these findings suggests that mindfulness may be associated with increased FC between two regions within the default network: the posterior cingulate cortex and the ventromedial prefrontal cortex. Additionally, extensive meditation experience may be associated with increased FC between the insula and the dorsolateral prefrontal cortex. However, little consensus has emerged within the existing literature owing to the diversity of operational definitions of mindfulness, neuroimaging methods, and network characterizations. We describe several challenges to develop a coherent cognitive neuroscience of mindfulness and to provide detailed recommendations for future research.", year = 2016, keywords = "2024-08-5-saved-papers;RePhD;RePhD/unread;meditation", doi = "10.1111/nyas.13044" } @ARTICLE{Guidotti2023-rc, title = "Long-Term and Meditation-Specific Modulations of Brain Connectivity Revealed Through Multivariate Pattern Analysis", author = "Guidotti, Roberto and D'Andrea, A and Basti, Alessio and Raffone, A and Pizzella, V and Marzetti, L", journal = "Brain Topogr.", volume = 36, pages = "409--418", abstract = "Neuroimaging studies have provided evidence that extensive meditation practice modifies the functional and structural properties of the human brain, such as large-scale brain region interplay. However, it remains unclear how different meditation styles are involved in the modulation of these large-scale brain networks. Here, using machine learning and fMRI functional connectivity, we investigated how focused attention and open monitoring meditation styles impact large-scale brain networks. Specifically, we trained a classifier to predict the meditation style in two groups of subjects: expert Theravada Buddhist monks and novice meditators. We showed that the classifier was able to discriminate the meditation style only in the expert group. Additionally, by inspecting the trained classifier, we observed that the Anterior Salience and the Default Mode networks were relevant for the classification, in line with their theorized involvement in emotion and self-related regulation in meditation. Interestingly, results also highlighted the role of specific couplings between areas crucial for regulating attention and self-awareness as well as areas related to processing and integrating somatosensory information. Finally, we observed a larger involvement of left inter-hemispheric connections in the classification. In conclusion, our work supports the evidence that extensive meditation practice modulates large-scale brain networks, and that the different meditation styles differentially affect connections that subserve style-specific functions.", year = 2023, keywords = "2024-08-5-saved-papers;RePhD;RePhD/unread;meditation", doi = "10.1007/s10548-023-00950-3" } @ARTICLE{Devaney2021-mg, title = "Attention and Default Mode Network Assessments of Meditation Experience during Active Cognition and Rest", author = "Devaney, Kathryn J and Levin, Emily J and Tripathi, Vaibhav and Higgins, James P and Lazar, Sara W and Somers, David C", journal = "Brain Sci", volume = 11, number = 5, abstract = "Meditation experience has previously been shown to improve performance on behavioral assessments of attention, but the neural bases of this improvement are unknown. Two prominent, strongly competing networks exist in the human cortex: a dorsal attention network, that is activated during focused attention, and a default mode network, that is suppressed during attentionally demanding tasks. Prior studies suggest that strong anti-correlations between these networks indicate good brain health. In addition, a third network, a ventral attention network, serves as a ``circuit-breaker'' that transiently disrupts and redirects focused attention to permit salient stimuli to capture attention. Here, we used functional magnetic resonance imaging to contrast cortical network activation between experienced focused attention Vipassana meditators and matched controls. Participants performed two attention tasks during scanning: a sustained attention task and an attention-capture task. Meditators demonstrated increased magnitude of differential activation in the dorsal attention vs. default mode network in a sustained attention task, relative to controls. In contrast, there were no evident attention network differences between meditators and controls in an attentional reorienting paradigm. A resting state functional connectivity analysis revealed a greater magnitude of anticorrelation between dorsal attention and default mode networks in the meditators as compared to both our local control group and a n = 168 Human Connectome Project dataset. These results demonstrate, with both task- and rest-based fMRI data, increased stability in sustained attention processes without an associated attentional capture cost in meditators. Task and resting-state results, which revealed stronger anticorrelations between dorsal attention and default mode networks in experienced mediators than in controls, are consistent with a brain health benefit of long-term meditation practice.", month = "29~" # apr, year = 2021, keywords = "Vipassana; attention; cognition; default mode network; dorsal attention network; fMRI; meditation; resting-state functional connectivity; ventral attention network;2024-08-5-saved-papers;RePhD;RePhD/unread;meditation;fMRI Attention", doi = "10.3390/brainsci11050566", language = "en" } @INCOLLECTION{Laukkonen2023-vm, title = "Chapter 4 - Cessations of consciousness in meditation: Advancing a scientific understanding of nirodha samāpatti", author = "Laukkonen, Ruben E and Sacchet, Matthew D and Barendregt, Henk and Devaney, Kathryn J and Chowdhury, Avijit and Slagter, Heleen A", editor = "Ben-Soussan, Tal Dotan and Glicksohn, Joseph and Srinivasan, Narayanan", booktitle = "Progress in Brain Research", publisher = "Elsevier", volume = 280, pages = "61--87", abstract = "Absence of consciousness can occur due to a concussion, anesthetization, intoxication, epileptic seizure, or other fainting/syncope episode caused by lack of blood flow to the brain. However, some meditation practitioners also report that it is possible to undergo a total absence of consciousness during meditation, lasting up to 7 days, and that these “cessations” can be consistently induced. One form of extended cessation (i.e., nirodha samāpatti) is thought to be different from sleep because practitioners are said to be completely impervious to external stimulation. That is, they cannot be 'woken up' from the cessation state as one might be from a dream. Cessations are also associated with the absence of any time experience or tiredness, and are said to involve a stiff rather than a relaxed body. Emergence from meditation-induced cessations is said to have profound effects on subsequent cognition and experience (e.g., resulting in a sudden sense of clarity, openness, and possibly insights). In this paper, we briefly outline the historical context for cessation events, present preliminary data from two labs, set a research agenda for their study, and provide an initial framework for understanding what meditation induced cessation may reveal about the mind and brain. We conclude by integrating these so-called nirodha and nirodha samāpatti experiences—as they are known in classical Buddhism—into current cognitive-neurocomputational and active inference frameworks of meditation.", month = "1~" # jan, year = 2023, keywords = "Consciousness; Meditation; Cessation; Awareness; Active inference; Predictive processing; Nirodha samāpatti; Jhāna; Fruition;2024-08-5-saved-papers;RePhD;RePhD/read;meditation;fMRI Attention;read", doi = "10.1016/bs.pbr.2022.12.007" } @ARTICLE{Saab2020-ec, title = "Weak supervision as an efficient approach for automated seizure detection in electroencephalography", author = "Saab, Khaled and Dunnmon, Jared and Ré, Christopher and Rubin, Daniel and Lee-Messer, Christopher", journal = "NPJ Digit Med", volume = 3, pages = 59, abstract = "Automated seizure detection from electroencephalography (EEG) would improve the quality of patient care while reducing medical costs, but achieving reliably high performance across patients has proven difficult. Convolutional Neural Networks (CNNs) show promise in addressing this problem, but they are limited by a lack of large labeled training datasets. We propose using imperfect but plentiful archived annotations to train CNNs for automated, real-time EEG seizure detection across patients. While these weak annotations indicate possible seizures with precision scores as low as 0.37, they are commonly produced in large volumes within existing clinical workflows by a mixed group of technicians, fellows, students, and board-certified epileptologists. We find that CNNs trained using such weak annotations achieve Area Under the Receiver Operating Characteristic curve (AUROC) values of 0.93 and 0.94 for pediatric and adult seizure onset detection, respectively. Compared to currently deployed clinical software, our model provides a 31\% increase (18 points) in F1-score for pediatric patients and a 17\% increase (11 points) for adult patients. These results demonstrate that weak annotations, which are sustainably collected via existing clinical workflows, can be leveraged to produce clinically useful seizure detection models.", month = "20~" # apr, year = 2020, keywords = "Computer science; Epilepsy;RePhD;EEG;Deep Learning;epilepsy", doi = "10.1038/s41746-020-0264-0", language = "en" } @ARTICLE{Rosenberg2015-mq, title = "A neuromarker of sustained attention from whole-brain functional connectivity", author = "Rosenberg, Monica D and Finn, Emily S and Scheinost, Dustin and Papademetris, Xenophon and Shen, Xilin and Constable, R Todd and Chun, Marvin M", journal = "Nat. Neurosci.", publisher = "Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.", volume = 19, pages = 165, abstract = "Although attention plays a ubiquitous role in perception and cognition, researchers lack a simple way to measure a person's overall attentional abilities. Because behavioral measures are diverse and difficult to standardize, we pursued a neuromarker of an important aspect of attention, sustained attention, using functional magnetic resonance imaging. To this end, we identified functional brain networks whose strength during a sustained attention task predicted individual differences in performance. Models based on these networks generalized to previously unseen individuals, even predicting performance from resting-state connectivity alone. Furthermore, these same models predicted a clinical measure of attention—symptoms of attention deficit hyperactivity disorder—from resting-state connectivity in an independent sample of children and adolescents. These results demonstrate that whole-brain functional network strength provides a broadly applicable neuromarker of sustained attention.", month = "23~" # nov, year = 2015, keywords = "RePhD;RePhD/gradCPT;RePhD/unread;attention;psych 210;fMRI Attention;ADHD", doi = "10.1038/nn.4179" } @ARTICLE{Hansen2007-wa, title = "Topographic organization in and near human visual area {V4}", author = "Hansen, Kathleen A and Kay, Kendrick N and Gallant, Jack L", journal = "J. Neurosci.", volume = 27, number = 44, pages = "11896--11911", abstract = "The existence and location of a human counterpart of macaque visual area V4 are disputed. To resolve this issue, we used functional magnetic resonance imaging to obtain topographic maps from human subjects, using visual stimuli and tasks designed to maximize accuracy of topographic maps of the fovea and parafovea and to measure the effects of attention on topographic maps. We identified multiple topographic transitions, each clearly visible in > or = 75\% of the maps, that we interpret as boundaries of distinct cortical regions. We call two of these regions dorsal V4 and ventral V4 (together comprising human area V4) because they share several defining characteristics with the macaque regions V4d and V4v (which together comprise macaque area V4). Ventral V4 is adjacent to V3v, and dorsal V4 is adjacent to parafoveal V3d. Ventral V4 and dorsal V4 meet in the foveal confluence shared by V1, V2, and V3. Ventral V4 and dorsal V4 represent complementary regions of the visual field, because ventral V4 represents the upper field and a subregion of the lower field, whereas dorsal V4 represents lower-field locations that are not represented by ventral V4. Finally, attentional modulation of spatial tuning is similar across dorsal and ventral V4, but attention has a smaller effect in V3d and V3v and a larger effect in a neighboring lateral occipital region.", month = "31~" # oct, year = 2007, keywords = "RePhD/read;RePhD;fMRI Vision;Quals", doi = "10.1523/JNEUROSCI.2991-07.2007", language = "en" }