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112


Medial prefrontal cortex supports perceptual memory [Letter]

Schwiedrzik, Caspar M; Sudmann, Sandrin S; Thesen, Thomas; Wang, Xiuyuan; Groppe, David M; Mégevand, Pierre; Doyle, Werner; Mehta, Ashesh D; Devinsky, Orrin; Melloni, Lucia
Our visual environment constantly changes, yet we experience the world as a stable, unified whole. How is this stability achieved? It has been proposed that the brain preserves an implicit perceptual memory in sensory cortices [1] which stabilizes perception towards previously experienced states [2,3]. The role of higher-order areas, especially prefrontal cortex (PFC), in perceptual memory is less explored. Because PFC exhibits long neural time constants, invariance properties, and large receptive fields which may stabilize perception against time-varying inputs, it seems particularly suited to implement perceptual memory [4]. Support for this idea comes from a neuroimaging study reporting that dorsomedial PFC (dmPFC) correlates with perceptual memory [5]. But dmPFC also participates in decision making [6], so its contribution to perceptual memory could arise on a post-perceptual, decisional level [7]. To determine which role, if any, PFC plays in perceptual memory, we obtained direct intracranial recordings in six epilepsy patients while they performed sequential orientation judgements on ambiguous stimuli known to elicit perceptual memory [8]. We found that dmPFC activity in the high gamma frequency band (HGB, 70-150 Hz) correlates with perceptual memory. This effect is anatomically specific to dmPFC and functionally specific for memories of preceding percepts. Further, dmPFC appears to play a causal role, as a patient with a lesion in this area showed impaired perceptual memory. Thus, dmPFC integrates current sensory information with prior percepts, stabilizing visual experience against the perpetual variability of our surroundings.
PMID: 30253147
ISSN: 1879-0445
CID: 3314272

Time-resolved neural reinstatement and pattern separation during memory decisions in human hippocampus

Lohnas, Lynn J; Duncan, Katherine; Doyle, Werner K; Thesen, Thomas; Devinsky, Orrin; Davachi, Lila
Mnemonic decision-making has long been hypothesized to rely on hippocampal dynamics that bias memory processing toward the formation of new memories or the retrieval of old ones. Successful memory encoding may be best optimized by pattern separation, whereby two highly similar experiences can be represented by underlying neural populations in an orthogonal manner. By contrast, successful memory retrieval is thought to be supported by a recovery of the same neural pattern laid down during encoding. Here we examined how hippocampal pattern completion and separation emerge over time during memory decisions. We measured electrocorticography activity in the human hippocampus and posterior occipitotemporal cortex (OTC) while participants performed continuous recognition of items that were new, repeated (old), or highly similar to a prior item (similar). During retrieval decisions of old items, both regions exhibited significant reinstatement of multivariate high-frequency activity (HFA) associated with encoding. Further, the extent of reinstatement of encoding patterns during retrieval was correlated with the strength (HFA power) of hippocampal encoding. Evidence for encoding pattern reinstatement was also seen in OTC on trials requiring fine-grained discrimination of similar items. By contrast, hippocampal activity showed evidence for pattern separation during these trials. Together, these results underscore the critical role of the hippocampus in supporting both reinstatement of overlapping information and separation of similar events.
PMCID:6077719
PMID: 30006465
ISSN: 1091-6490
CID: 3192792

Focal Cortical Anomalies and Language Impairment in 16p11.2 Deletion and Duplication Syndrome

Blackmon, Karen; Thesen, Thomas; Green, Sophie; Ben-Avi, Emma; Wang, Xiuyuan; Fuchs, Benjamin; Kuzniecky, Ruben; Devinsky, Orrin
Individuals with copy number variants (CNV) in the 16p11.2 chromosomal region are at high risk for language disorders. We investigate whether the extent and location of focal cortical anomalies are associated with language impairment in individuals with 16p11.2 CNVs. High-resolution T1-weighted MRI scans from 30 16p11.2 deletion (16p-del), 25 16p11.2 duplication (16p-dup), and 90 noncarrier controls (NCC) were analyzed to derive personalized cortical anomaly maps through single-case cortical thickness (CT) comparison to age-matched normative samples. Focal cortical anomalies were elevated in both 16p-del and 16p-dup and their total extent was inversely correlated with Full-Scale IQ. Clusters of abnormally thick cortex were more extensive in the 16p-del group and clusters of abnormally thin cortex were more extensive in the 16p-dup group. Abnormally thick clusters were more extensive in left lateral temporal and bilateral postcentral and mesial occipital regions in 16p-del. Focal cortical anomalies in the left middle temporal region and pars opercularis (Broca's region) of children with 16-del were associated with lower scores on a comprehensive language evaluation. Results extend neuroanatomical findings in 16p11.2 syndrome to include spatially heterogenous focal cortical anomalies that appear to disrupt language ability in accordance with the functional specialization of left frontotemporal regions.
PMID: 28591836
ISSN: 1460-2199
CID: 2592152

Functional brain connectivity is predictable from anatomic network's Laplacian eigen-structure

Abdelnour, Farras; Dayan, Michael; Devinsky, Orrin; Thesen, Thomas; Raj, Ashish
How structural connectivity (SC) gives rise to functional connectivity (FC) is not fully understood. Here we mathematically derive a simple relationship between SC measured from diffusion tensor imaging, and FC from resting state fMRI. We establish that SC and FC are related via (structural) Laplacian spectra, whereby FC and SC share eigenvectors and their eigenvalues are exponentially related. This gives, for the first time, a simple and analytical relationship between the graph spectra of structural and functional networks. Laplacian eigenvectors are shown to be good predictors of functional eigenvectors and networks based on independent component analysis of functional time series. A small number of Laplacian eigenmodes are shown to be sufficient to reconstruct FC matrices, serving as basis functions. This approach is fast, and requires no time-consuming simulations. It was tested on two empirical SC/FC datasets, and was found to significantly outperform generative model simulations of coupled neural masses.
PMID: 29454104
ISSN: 1095-9572
CID: 2990642

Parieto-frontal gyrification and working memory in healthy adults

Green, Sophie; Blackmon, Karen; Thesen, Thomas; DuBois, Jonathan; Wang, Xiuyuan; Halgren, Eric; Devinsky, Orrin
Gyrification of the cortical mantle is a dynamic process that increases with cortical surface area and decreases with age. Increased gyrification is associated with higher scores on cognitive tasks in adults; however, the degree to which this relationship is independent of cortical surface area remains undefined. This study investigates whether regional variation in gyrification is associated with domain-general and domain-specific cognition. Our hypothesis is that increased local gyrification confers a functional advantage that is independent of surface area. To quantify regional gyrification, we computed the local gyrification index (LGI) at each vertex and averaged across a bilateral parietal-frontal region associated with general intelligence and reasoning (Jung and Haier 2007). A sample of 48 healthy adults (24 males/24 females; ages 18-68 years) completed a high-resolution 3 T T1-weighted MRI and standardized administration of the Wechsler Adult Intelligence Scale (WAIS). We found a positive correlation between cortical gyrification and working memory, which remained significant after controlling for cortical surface area. Results suggest that a higher degree of local cortical folding confers a functional advantage that is independent from surface area and evident for more dynamic or "fluid" cognitive processes (i.e., working memory) rather than over-learned or "crystallized" cognitive processes.
PMID: 28290070
ISSN: 1931-7565
CID: 2489872

Author Correction: Low frequency transcranial electrical stimulation does not entrain sleep rhythms measured by human intracranial recordings [Correction]

Lafon, Belen; Henin, Simon; Huang, Yu; Friedman, Daniel; Melloni, Lucia; Thesen, Thomas; Doyle, Werner; Buzsaki, Gyorgy; Devinsky, Orrin; Parra, Lucas C; Liu, Anli
It has come to our attention that we did not specify whether the stimulation magnitudes we report in this Article are peak amplitudes or peak-to-peak. All references to intensity given in mA in the manuscript refer to peak-to-peak amplitudes, except in Fig. 2, where the model is calibrated to 1 mA peak amplitude, as stated. In the original version of the paper we incorrectly calibrated the computational models to 1 mA peak-to-peak, rather than 1 mA peak amplitude. This means that we divided by a value twice as large as we should have. The correct estimated fields are therefore twice as large as shown in the original Fig. 2 and Supplementary Figure 11. The corrected figures are now properly calibrated to 1 mA peak amplitude. Furthermore, the sentence in the first paragraph of the Results section 'Intensity ranged from 0.5 to 2.5 mA (current density 0.125-0.625 mA mA/cm2), which is stronger than in previous reports', should have read 'Intensity ranged from 0.5 to 2.5 mA peak to peak (peak current density 0.0625-0.3125 mA/cm2), which is stronger than in previous reports.' These errors do not affect any of the Article's conclusions.
PMCID:5830401
PMID: 29491347
ISSN: 2041-1723
CID: 2965562

Structural brain abnormalities in the common epilepsies assessed in a worldwide ENIGMA study

Whelan, Christopher D; Altmann, Andre; Botía, Juan A; Jahanshad, Neda; Hibar, Derrek P; Absil, Julie; Alhusaini, Saud; Alvim, Marina K M; Auvinen, Pia; Bartolini, Emanuele; Bergo, Felipe P G; Bernardes, Tauana; Blackmon, Karen; Braga, Barbara; Caligiuri, Maria Eugenia; Calvo, Anna; Carr, Sarah J; Chen, Jian; Chen, Shuai; Cherubini, Andrea; David, Philippe; Domin, Martin; Foley, Sonya; França, Wendy; Haaker, Gerrit; Isaev, Dmitry; Keller, Simon S; Kotikalapudi, Raviteja; Kowalczyk, Magdalena A; Kuzniecky, Ruben; Langner, Soenke; Lenge, Matteo; Leyden, Kelly M; Liu, Min; Loi, Richard Q; Martin, Pascal; Mascalchi, Mario; Morita, Marcia E; Pariente, Jose C; Rodríguez-Cruces, Raul; Rummel, Christian; Saavalainen, Taavi; Semmelroch, Mira K; Severino, Mariasavina; Thomas, Rhys H; Tondelli, Manuela; Tortora, Domenico; Vaudano, Anna Elisabetta; Vivash, Lucy; von Podewils, Felix; Wagner, Jan; Weber, Bernd; Yao, Yi; Yasuda, Clarissa L; Zhang, Guohao; Bargalló, Nuria; Bender, Benjamin; Bernasconi, Neda; Bernasconi, Andrea; Bernhardt, Boris C; Blümcke, Ingmar; Carlson, Chad; Cavalleri, Gianpiero L; Cendes, Fernando; Concha, Luis; Delanty, Norman; Depondt, Chantal; Devinsky, Orrin; Doherty, Colin P; Focke, Niels K; Gambardella, Antonio; Guerrini, Renzo; Hamandi, Khalid; Jackson, Graeme D; Kälviäinen, Reetta; Kochunov, Peter; Kwan, Patrick; Labate, Angelo; McDonald, Carrie R; Meletti, Stefano; O'Brien, Terence J; Ourselin, Sebastien; Richardson, Mark P; Striano, Pasquale; Thesen, Thomas; Wiest, Roland; Zhang, Junsong; Vezzani, Annamaria; Ryten, Mina; Thompson, Paul M; Sisodiya, Sanjay M
Progressive functional decline in the epilepsies is largely unexplained. We formed the ENIGMA-Epilepsy consortium to understand factors that influence brain measures in epilepsy, pooling data from 24 research centres in 14 countries across Europe, North and South America, Asia, and Australia. Structural brain measures were extracted from MRI brain scans across 2149 individuals with epilepsy, divided into four epilepsy subgroups including idiopathic generalized epilepsies (n =367), mesial temporal lobe epilepsies with hippocampal sclerosis (MTLE; left, n = 415; right, n = 339), and all other epilepsies in aggregate (n = 1026), and compared to 1727 matched healthy controls. We ranked brain structures in order of greatest differences between patients and controls, by meta-analysing effect sizes across 16 subcortical and 68 cortical brain regions. We also tested effects of duration of disease, age at onset, and age-by-diagnosis interactions on structural measures. We observed widespread patterns of altered subcortical volume and reduced cortical grey matter thickness. Compared to controls, all epilepsy groups showed lower volume in the right thalamus (Cohen's d = -0.24 to -0.73; P < 1.49 × 10-4), and lower thickness in the precentral gyri bilaterally (d = -0.34 to -0.52; P < 4.31 × 10-6). Both MTLE subgroups showed profound volume reduction in the ipsilateral hippocampus (d = -1.73 to -1.91, P < 1.4 × 10-19), and lower thickness in extrahippocampal cortical regions, including the precentral and paracentral gyri, compared to controls (d = -0.36 to -0.52; P < 1.49 × 10-4). Thickness differences of the ipsilateral temporopolar, parahippocampal, entorhinal, and fusiform gyri, contralateral pars triangularis, and bilateral precuneus, superior frontal and caudal middle frontal gyri were observed in left, but not right, MTLE (d = -0.29 to -0.54; P < 1.49 × 10-4). Contrastingly, thickness differences of the ipsilateral pars opercularis, and contralateral transverse temporal gyrus, were observed in right, but not left, MTLE (d = -0.27 to -0.51; P < 1.49 × 10-4). Lower subcortical volume and cortical thickness associated with a longer duration of epilepsy in the all-epilepsies, all-other-epilepsies, and right MTLE groups (beta, b < -0.0018; P < 1.49 × 10-4). In the largest neuroimaging study of epilepsy to date, we provide information on the common epilepsies that could not be realistically acquired in any other way. Our study provides a robust ranking of brain measures that can be further targeted for study in genetic and neuropathological studies. This worldwide initiative identifies patterns of shared grey matter reduction across epilepsy syndromes, and distinctive abnormalities between epilepsy syndromes, which inform our understanding of epilepsy as a network disorder, and indicate that certain epilepsy syndromes involve more widespread structural compromise than previously assumed.
PMCID:5837616
PMID: 29365066
ISSN: 1460-2156
CID: 2929252

Patient-Specific Pose Estimation in Clinical Environments

Chen, Kenny; Gabriel, Paolo; Alasfour, Abdulwahab; Gong, Chenghao; Doyle, Werner K; Devinsky, Orrin; Friedman, Daniel; Dugan, Patricia; Melloni, Lucia; Thesen, Thomas; Gonda, David; Sattar, Shifteh; Wang, Sonya; Gilja, Vikash
Reliable posture labels in hospital environments can augment research studies on neural correlates to natural behaviors and clinical applications that monitor patient activity. However, many existing pose estimation frameworks are not calibrated for these unpredictable settings. In this paper, we propose a semi-automated approach for improving upper-body pose estimation in noisy clinical environments, whereby we adapt and build around an existing joint tracking framework to improve its robustness to environmental uncertainties. The proposed framework uses subject-specific convolutional neural network models trained on a subset of a patient's RGB video recording chosen to maximize the feature variance of each joint. Furthermore, by compensating for scene lighting changes and by refining the predicted joint trajectories through a Kalman filter with fitted noise parameters, the extended system yields more consistent and accurate posture annotations when compared with the two state-of-the-art generalized pose tracking algorithms for three hospital patients recorded in two research clinics.
PMCID:6255526
PMID: 30483453
ISSN: 2168-2372
CID: 3500622

Replay of large-scale spatio-temporal patterns from waking during subsequent NREM sleep in human cortex

Jiang, Xi; Shamie, Isaac; K Doyle, Werner; Friedman, Daniel; Dugan, Patricia; Devinsky, Orrin; Eskandar, Emad; Cash, Sydney S; Thesen, Thomas; Halgren, Eric
Animal studies support the hypothesis that in slow-wave sleep, replay of waking neocortical activity under hippocampal guidance leads to memory consolidation. However, no intracranial electrophysiological evidence for replay exists in humans. We identified consistent sequences of population firing peaks across widespread cortical regions during complete waking periods. The occurrence of these "Motifs" were compared between sleeps preceding the waking period ("Sleep-Pre") when the Motifs were identified, and those following ("Sleep-Post"). In all subjects, the majority of waking Motifs (most of which were novel) had more matches in Sleep-Post than in Sleep-Pre. In rodents, hippocampal replay occurs during local sharp-wave ripples, and the associated neocortical replay tends to occur during local sleep spindles and down-to-up transitions. These waves may facilitate consolidation by sequencing cell-firing and encouraging plasticity. Similarly, we found that Motifs were coupled to neocortical spindles, down-to-up transitions, theta bursts, and hippocampal sharp-wave ripples. While Motifs occurring during cognitive task performance were more likely to have more matches in subsequent sleep, our studies provide no direct demonstration that the replay of Motifs contributes to consolidation. Nonetheless, these results confirm a core prediction of the dominant neurobiological theory of human memory consolidation.
PMCID:5727134
PMID: 29234075
ISSN: 2045-2322
CID: 2844352

Low frequency transcranial electrical stimulation does not entrain sleep rhythms measured by human intracranial recordings

Lafon, Belen; Henin, Simon; Huang, Yu; Friedman, Daniel; Melloni, Lucia; Thesen, Thomas; Doyle, Werner; Buzsaki, Gyorgy; Devinsky, Orrin; Parra, Lucas C; A Liu, Anli
Transcranial electrical stimulation has widespread clinical and research applications, yet its effect on ongoing neural activity in humans is not well established. Previous reports argue that transcranial alternating current stimulation (tACS) can entrain and enhance neural rhythms related to memory, but the evidence from non-invasive recordings has remained inconclusive. Here, we measure endogenous spindle and theta activity intracranially in humans during low-frequency tACS and find no stable entrainment of spindle power during non-REM sleep, nor of theta power during resting wakefulness. As positive controls, we find robust entrainment of spindle activity to endogenous slow-wave activity in 66% of electrodes as well as entrainment to rhythmic noise-burst acoustic stimulation in 14% of electrodes. We conclude that low-frequency tACS at common stimulation intensities neither acutely modulates spindle activity during sleep nor theta activity during waking rest, likely because of the attenuated electrical fields reaching the cortical surface.
PMCID:5662600
PMID: 29084960
ISSN: 2041-1723
CID: 2765082