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Subanesthetic doses of ketamine induce an antidepressant effect within hours in individuals with treatment-resistant depression while it furthermore induces immediate but transient psychotomimetic effects. Among these psychotomimetic effects, an altered sense of self has specifically been associated with the antidepressant response to ketamine as well as psychedelics. However, there is plenty of variation in the extent of the drug-induced altered sense of self experience that might be explained by differences in basal morphological characteristics, such as cortical thickness. Regions that have been previously associated with a psychedelics-induced sense of self and with ketamine’s mechanism of action, are the posterior cingulate cortex (PCC) and the pregenual anterior cingulate cortex (pgACC).In this randomized, placebo-controlled, double-blind cross-over magnetic resonance imaging study, thirty-five healthy male participants (mean age±standard deviation (SD)=25.1±4.2 years) were scanned at 7 T. We investigated whether the cortical thickness of two DMN regions, the PCC and the pgACC, are associated with disembodiment and experience of unity scores, which were used to index the ketamine-induced altered sense of self. We observed a negative correlation between the PCC cortical thickness and the disembodiment scores. In contrast, no significant association was found between the pgACC cortical thickness and the ketamine-induced altered sense of self. In the context of the existing literature, our findings highlight the importance of the PCC as a structure involved in the mechanism of ketamine-induced altered sense of self that seems to be shared with different antidepressant agents with psychotomimetic effects operating on different classes of transmitter systems.

Background: Social anxiety disorder is characterized by intense fear and avoidance of social interactions and scrutiny by others. Although alterations in attentional control seem to play a central role in the psychopathology of social anxiety disorder, the neural underpinnings in prefrontal brain regions have not yet been fully clarified. Methods: The present study used functional MRI in participants (age 18–50 yr) with social anxiety disorder (n = 42, 31 female) and without (n = 58, 33 female). It investigated the interrelation of the effects of social anxiety disorder and early-life adversity (a main environmental risk factor of social anxiety disorder) on brain activity during an attentional control task. We applied DNA methylation analysis to determine whether epigenetic modulation in the gene encoding the glucocorticoid receptor, NR3C1, might play a mediating role in this process. Results: We identified 2 brain regions in the left and medial prefrontal cortex that exhibited an interaction effect of social anxiety disorder and early-life adversity. In participants with low levels of early-life adversity, neural activity in response to disorder-related stimuli was increased in association with social anxiety disorder. In participants with high levels of early-life adversity, neural activity was increased only in participants without social anxiety disorder. NR3C1 DNA methylation partly mediated the effect of social anxiety disorder on brain activity as a function of early-life adversity. Limitations: The absence of behavioural correlates associated with social anxiety disorder limited functional interpretation of the results. Conclusion: These findings demonstrate that the neurobiological processes that underlie social anxiety disorder might be fundamentally different depending on experiences of early-life adversity. Long-lasting effects of early-life adversity might be encoded in NR3C1 DNA methylation and entail alterations in social anxiety disorder–related activity patterns in the neural network of attentional control.

Social anxiety disorder (SAD) is a psychiatric disorder characterized by severe fear in social situations and avoidance of these. Multiple genetic as well as environmental factors contribute to the etiopathology of SAD. One of the main risk factors for SAD is stress, especially during early periods of life (early life adversity; ELA). ELA leads to structural and regulatory alterations contributing to disease vulnerability. This includes the dysregulation of the immune response. However, the molecular link between ELA and the risk for SAD in adulthood remains largely unclear. Evidence is emerging that long-lasting changes of gene expression patterns play an important role in the biological mechanisms linking ELA and SAD. Therefore, we conducted a transcriptome study of SAD and ELA performing RNA sequencing in peripheral blood samples. Analyzing differential gene expression between individuals suffering from SAD with high or low levels of ELA and healthy individuals with high or low levels of ELA, 13 significantly differentially expressed genes (DEGs) were identified with respect to SAD while no significant differences in expression were identified with respect to ELA. The most significantly expressed gene was MAPK3 (p = 0.003) being upregulated in the SAD group compared to control individuals. In contrary, weighted gene co-expression network analysis (WGCNA) identified only modules significantly associated with ELA (p ≤ 0.05), not with SAD. Furthermore, analyzing interaction networks of the genes from the ELA-associated modules and the SAD-related MAPK3 revealed complex interactions of those genes. Gene functional enrichment analyses indicate a role of signal transduction pathways as well as inflammatory responses supporting an involvement of the immune system in the association of ELA and SAD. In conclusion, we did not identify a direct molecular link between ELA and adult SAD by transcriptional changes. However, our data indicate an indirect association of ELA and SAD mediated by the interaction of genes involved in immune-related signal transduction.

Several Alzheimer’s disease (AD) atrophy subtypes were identified, but their brain network properties are unclear. We analyzed data from two independent datasets, including 166 participants (103 AD/63 controls) from the DZNE-longitudinal cognitive impairment and dementia study and 151 participants (121 AD/30 controls) from the AD neuroimaging initiative cohorts, aiming to identify differences between AD atrophy subtypes in resting-state functional magnetic resonance imaging intra-network connectivity (INC) and global and nodal network properties. Using a data-driven clustering approach, we identified four AD atrophy subtypes with differences in functional connectivity, accompanied by clinical and biomarker alterations, including a medio-temporal-predominant (S-MT), a limbic-predominant (S-L), a diffuse (S-D), and a mild-atrophy (S-MA) subtype. S-MT and S-D showed INC reduction in the default mode, dorsal attention, visual and limbic network, and a pronounced reduction of “global efficiency” and decrease of the “clustering coefficient” in parietal and temporal lobes. Despite severe atrophy in limbic areas, the S-L exhibited only marginal global network but substantial nodal network failure. S-MA, in contrast, showed limited impairment in clinical and cognitive scores but pronounced global network failure. Our results contribute toward a better understanding of heterogeneity in AD with the detection of distinct differences in functional connectivity networks accompanied by CSF biomarker and cognitive differences in AD subtypes.

ObjectiveTo determine whether following a Mediterranean-like diet (MeDi) relates to cognitive functions and in vivo biomarkers for Alzheimer disease (AD), we analyzed cross-sectional data from the German DZNE-Longitudinal Cognitive Impairment and Dementia Study.MethodThe sample (n = 512, mean age 69.5 ± 5.9 years) included 169 cognitively normal participants and individuals at higher AD risk (53 with relatives with AD, 209 with subjective cognitive decline, and 81 with mild cognitive impairment). We defined MeDi adherence according to the food frequency questionnaire. Brain volume outcomes were generated via voxel-based morphometry on T1-MRI, and cognitive performance was assessed with an extensive neuropsychological battery. AD-related biomarkers (β-amyloid42/40 [Aβ42/40] ratio, phosphorylated tau 181 [pTau181]) in CSF were assessed in n = 226 individuals. We analyzed the associations between MeDi and outcomes with linear regression models controlling for several covariates. In addition, we applied hypothesis-driven mediation and moderation analysis.ResultsHigher MeDi adherence related to larger mediotemporal gray matter volume (p < 0.05 family-wise error corrected), better memory (β ± SE = 0.03 ± 0.02; p = 0.038), and less amyloid (Aβ42/40 ratio, β ± SE = 0.003 ± 0.001; p = 0.008) and pTau181 (β ± SE = −1.96 ± 0.68; p = 0.004) pathology. Mediotemporal volume mediated the association between MeDi and memory (40% indirect mediation). Finally, MeDi favorably moderated the associations among Aβ42/40 ratio, pTau181, and mediotemporal atrophy. Results were consistent correcting for APOE-ε4 status.ConclusionOur findings corroborate the view of MeDi as a protective factor against memory decline and mediotemporal atrophy. They suggest that these associations might be explained by a decrease of amyloidosis and tau pathology. Longitudinal and dietary intervention studies should further examine this conjecture and its treatment implications.

Subjective tinnitus is the conscious perception of sound in the absence of any acoustic source. The literature suggests various tinnitus mechanisms, most of which invoke changes in spontaneous firing rates of central auditory neurons resulting from modification of neural gain. Here, we present an alternative model based on evidence that tinnitus is: (1) rare in people who are congenitally deaf, (2) common in people with acquired deafness, and (3) potentially suppressed by active cochlear implants used for hearing restoration. We propose that tinnitus can only develop after fast auditory fiber activity has stimulated the synapse formation between fast-spiking parvalbumin positive (PV1) interneurons and projecting neurons in the ascending auditory path and coactivated frontostriatal networks after hearing onset. Thereafter, fast auditory fiber activity promotes feedforward and feedback inhibition mediated by PV1 interneuron activity in auditory-specific circuits. This inhibitory network enables enhanced stimulus resolution, attention-driven contrast improvement, and augmentation of auditory responses in central auditory pathways (neural gain) after damage of slow auditory fibers. When fast auditory fiber activity is lost, tonic PV1 interneuron activity is diminished, resulting in the prolonged response latencies, sudden hyperexcitability, enhanced cortical synchrony, elevated spontaneous c oscillations, and impaired attention/stress-control that have been described in previous tinnitus models. Moreover, because fast processing is gained through sensory experience, tinnitus would not exist in congenital deafness. Electrical cochlear stimulation may have the potential to reestablish tonic inhibitory networks and thus suppress tinnitus. The proposed framework unites many ideas of tinnitus pathophysiology and may catalyze cooperative efforts to develop tinnitus therapies.

Highlights • Composite scores provide reliable metrics of domain function in multicenter cohort. • Visuo-spatial domain composite scores relate to anatomic changes in AD spectrum. • Domain scores relate to network-specific resting-state connectivity in AD spectrum., Background Cognitive decline has been found to be associated with gray matter atrophy and disruption of functional neural networks in Alzheimer’s disease (AD) in structural and functional imaging (fMRI) studies. Most previous studies have used single test scores of cognitive performance among monocentric cohorts. However, cognitive domain composite scores could be more reliable than single test scores due to the reduction of measurement error. Adopting a multicentric resting state fMRI (rs-fMRI) and cognitive domain approach, we provide a comprehensive description of the structural and functional correlates of the key cognitive domains of AD. Method We analyzed MRI, rs-fMRI and cognitive domain score data of 490 participants from an interim baseline release of the multicenter DELCODE study cohort, including 54 people with AD, 86 with Mild Cognitive Impairment (MCI), 175 with Subjective Cognitive Decline (SCD), and 175 Healthy Controls (HC) in the AD-spectrum. Resulting cognitive domain composite scores (executive, visuo-spatial, memory, working memory and language) from the DELCODE neuropsychological battery (DELCODE-NP), were previously derived using confirmatory factor analysis. Statistical analyses examined the differences between diagnostic groups, and the association of composite scores with regional atrophy and network-specific functional connectivity among the patient subgroup of SCD, MCI and AD. Result Cognitive performance, atrophy patterns and functional connectivity significantly differed between diagnostic groups in the AD-spectrum. Regional gray matter atrophy was positively associated with visuospatial and other cognitive impairments among the patient subgroup in the AD-spectrum. Except for the visual network, patterns of network-specific resting-state functional connectivity were positively associated with distinct cognitive impairments among the patient subgroup in the AD-spectrum. Conclusion Consistent associations between cognitive domain scores and both regional atrophy and network-specific functional connectivity (except for the visual network), support the utility of a multicentric and cognitive domain approach towards explicating the relationship between imaging markers and cognition in the AD-spectrum.

Background: Although convolutional neural networks (CNN) achieve high diagnostic accuracy for detecting Alzheimer's disease (AD) dementia based on magnetic resonance imaging (MRI) scans, they are not yet applied in clinical routine. One important reason for this is a lack of model comprehensibility. Recently developed visualization methods for deriving CNN relevance maps may help to fill this gap. We investigated whether models with higher accuracy also rely more on discriminative brain regions predefined by prior knowledge. Methods: We trained a CNN for the detection of AD in N=663 T1-weighted MRI scans of patients with dementia and amnestic mild cognitive impairment (MCI) and verified the accuracy of the models via cross-validation and in three independent samples including N=1655 cases. We evaluated the association of relevance scores and hippocampus volume to validate the clinical utility of this approach. To improve model comprehensibility, we implemented an interactive visualization of 3D CNN relevance maps. Results: Across three independent datasets, group separation showed high accuracy for AD dementia vs. controls (AUC$\geq$0.92) and moderate accuracy for MCI vs. controls (AUC$\approx$0.75). Relevance maps indicated that hippocampal atrophy was considered as the most informative factor for AD detection, with additional contributions from atrophy in other cortical and subcortical regions. Relevance scores within the hippocampus were highly correlated with hippocampal volumes (Pearson's r$\approx$-0.86, p, 24 pages, 9 figures/tables, supplementary material, source code available on GitHub

Social anxiety disorder (SAD) is a psychiatric disorder characterized by extensive fear in social situations. Multiple genetic and environmental factors are known to contribute to its pathogenesis. One of the main environmental risk factors is early life adversity (ELA). Evidence is emerging that epigenetic mechanisms such as DNA methylation might play an important role in the biological mechanisms underlying SAD and ELA. To investigate the relationship between ELA, DNA methylation, and SAD, we performed an epigenome-wide association study for SAD and ELA examining DNA from whole blood of a cohort of 143 individuals using DNA methylation arrays. We identified two differentially methylated regions (DMRs) associated with SAD located within the genes SLC43A2 and TNXB. As this was the first epigenome-wide association study for SAD, it is worth noting that both genes have previously been associated with panic disorder. Further, we identified two DMRs associated with ELA within the SLC17A3 promoter region and the SIAH3 gene and several DMRs that were associated with the interaction of SAD and ELA. Of these, the regions within C2CD2L and MRPL28 showed the largest difference in DNA methylation. Lastly, we found that two DMRs were associated with both the severity of social anxiety and ELA, however, neither of them was found to mediate the contribution of ELA to SAD later in life. Future studies are needed to replicate our findings in independent cohorts and to investigate the biological pathways underlying these effects.

Background There is growing evidence in the literature that the cholinergic basal forebrain might be one of the earliest affected structures in Alzheimer’s disease (AD). Recent data suggest that individuals with preclinical Alzheimer’s pathology already show atrophy of the posterior nucleus basalis of Meynert and that this even precedes the atrophy of the entorhinal cortex. Here we investigated whether basal forebrain volume reductions might not only be detectable in the mild cognitive impairment (MCI) and dementia stage of AD, but also in subjective cognitive decline (SCD) individuals who represent an at-risk population for preclinical AD, and examine the relationship with cognitive performance and amyloid-beta pathology. Methods Basal forebrain volumes of 341 participants from the multi-center German Center for Neurodegenerative Diseases Longitudinal Cognitive Impairment and Dementia Study, including 135 healthy controls, 110 SCD, 60 MCI, and 36 AD, were analyzed using high-resolution T1-weighted images. Healthy controls and SCD participants were further grouped into amyloid-positive and amyloid-negative cases according to their cerebrospinal fluid Aβ42/40 ratio. Associations between basal forebrain volume, neuropsychological performance, and amyloid load were evaluated. Results Apart from confirming progressive basal forebrain atrophy from MCI to AD, atrophy of the posterior of nucleus basalis of Meynert was also observed in subjective cognitive decline with confirmed evidence for preclinical Alzheimer’s pathology, based on the Aβ42/40 ratio. This atrophy was neither evident in subjects with SCD without amyloid pathology nor in healthy controls with amyloid pathology. Additionally, the volume of the posterior of nucleus basalis of Meynert was significantly correlated with amyloid Aβ42/40 ratio in SCD but not in healthy controls. Conclusion Our results confirm that basal forebrain atrophy occurs early along the Alzheimer’s disease trajectory. The observed volume reduction of the cholinergic basal forebrain in Aβ-positive participants with subjective cognitive complains and the absence of any volume reductions in the Aβ-positive healthy controls suggests that these ‘subjective cognitive decline’ symptoms reflect progression from stage 1 (asymptomatic) to stage 2 (transitional cognitive impairment) of the Alzheimer’s continuum (according to the recent National Institute on Aging-Alzheimer’s Association Research Framework), revealing the beginning neurodegeneration on a macroscopic level.

Significance Learning is thought to be mediated by activity-dependent modification of neuronal interactions. To avoid maladaptive modifications of synaptic transmission by spurious activity, synaptic plasticity has to be gated. In the case of supervised learning, these gating functions are accomplished by reinforcement through value-assigning systems. Here we show that the dynamic state of local circuits correlates with the occurrence of activity-dependent long-term changes in neuronal response properties. We find that repeated visual stimuli induce long-term changes of orientation preference of neuronal populations in visual cortex if stimuli induce synchronized population responses oscillating at ɣ-frequencies. This suggests that neuronal plasticity is controlled by a hierarchy of gating systems and assigns critical gating functions to resonance properties of local circuits., Use-dependent long-term changes of neuronal response properties must be gated to prevent irrelevant activity from inducing inappropriate modifications. Here we test the hypothesis that local network dynamics contribute to such gating. As synaptic modifications depend on temporal contiguity between presynaptic and postsynaptic activity, we examined the effect of synchronized gamma (ɣ) oscillations on stimulation-dependent modifications of orientation selectivity in adult cat visual cortex. Changes of orientation maps were induced by pairing visual stimulation with electrical activation of the mesencephalic reticular formation. Changes in orientation selectivity were assessed with optical recording of intrinsic signals and multiunit recordings. When conditioning stimuli were associated with strong ɣ-oscillations, orientation domains matching the orientation of the conditioning grating stimulus became more responsive and expanded, because neurons with preferences differing by less than 30° from the orientation of the conditioning grating shifted their orientation preference toward the conditioned orientation. When conditioning stimuli induced no or only weak ɣ-oscillations, responsiveness of neurons driven by the conditioning stimulus decreased. These differential effects depended on the power of oscillations in the low ɣ-band (20 Hz to 48 Hz) and not on differences in discharge rate of cortical neurons, because there was no correlation between the discharge rates during conditioning and the occurrence of changes in orientation preference. Thus, occurrence and polarity of use-dependent long-term changes of cortical response properties appear to depend on the occurrence of ɣ-oscillations during induction and hence on the degree of temporal coherence of the change-inducing network activity.

We are used to dealing with concepts which provide explanations for how cognitive processes are initiated. But we hardly ever spend time on trying to explain how such processes are turned off again and, thus, do not compromise subsequent processes.

Background: Ketamine is receiving increasing attention as a rapid-onset antidepressant in patients suffering from major depressive disorder (MDD) with treatment resistance or severe suicidal ideation. Ketamine modulates several neurotransmitter systems, including norepinephrine via the norepinephrine transporter (NET), both peripherally and centrally. The locus coeruleus (LC), which has high NET concentration, has been attributed to brain networks involved in depression. Thus we investigated the effects of single-dose of racemic ketamine on the LC using resting state functional MRI. Methods: Fifty-nine healthy participants (mean age 25.57 ± 4.72) were examined in a double-blind, randomized, placebo-controlled study with 7 Tesla MRI. We investigated the resting state functional connectivity (rs-fc) of the LC before and one hour after subanesthetic ketamine injection (0.5 mg/kg), as well as associations between its rs-fc and a common polymorphism in the NET gene (rs28386840). Results: A significant interaction of drug and time was revealed, and post hoc testing showed decreased rs-fc between LC and the thalamus after ketamine administration compared with baseline levels, including the mediodorsal, ventral anterior, ventral lateral, ventral posterolateral and centromedian nuclei. The rs-fc reduction was more pronounced in NET rs28386840 [AA] homozygous subjects than in [T] carriers. Conclusions: We demonstrated acute rs-fc changes after ketamine administration in the central node of the norepinephrine pathway. These findings may contribute to understanding the antidepressant effect of ketamine at the system level, supporting modes of action on networks subserving aberrant arousal regulation in depression. Keywords: Ketamine, Locus coeruleus (LC), Norepinephrine transporter (NET), Attention networks, Pharmacogenetics, Major depressive disorder (MDD)

In primates, posterior auditory cortical areas are thought to be part of a dorsal auditory pathway that processes spatial information. But how posterior (and other) auditory areas represent acoustic space remains a matter of debate. Here we provide new evidence based on functional magnetic resonance imaging (fMRI) of the macaque indicating that space is predominantly represented by a distributed hemifield code rather than by a local spatial topography. Hemifield tuning in cortical and subcortical regions emerges from an opponent hemispheric pattern of activation and deactivation that depends on the availability of interaural delay cues. Importantly, these opponent signals allow responses in posterior regions to segregate space similarly to a hemifield code representation. Taken together, our results reconcile seemingly contradictory views by showing that the representation of space follows closely a hemifield code and suggest that enhanced posterior-dorsal spatial specificity in primates might emerge from this form of coding.

We are used to dealing with concepts which provide explanations for how cognitive processes are initiated. But we hardly ever spend time on trying to explain how such processes are turned off again and, thus, do not compromise subsequent processes.

Event-related potentials (ERPs) are widely used in basic neuroscience and in clinical diagnostic procedures. In contrast, neurophysiological insights from ERPs have been limited, as several different mechanisms lead to ERPs. Apart from stereotypically repeated responses (additive evoked responses), these mechanisms are asymmetric amplitude modulations and phase-resetting of ongoing oscillatory activity. Therefore, a method is needed that differentiates between these mechanisms and moreover quantifies the stability of a response. We propose a constrained subspace independent component analysis that exploits the multivariate information present in the all-to-all relationship of recordings over trials. Our method identifies additive evoked activity and quantifies its stability over trials. We evaluate identification performance for biologically plausible simulation data and two neurophysiological test cases: Local field potential (LFP) recordings from a visuo-motor-integration task in the awake behaving macaque and magnetoencephalography (MEG) recordings of steady-state visual evoked fields (SSVEFs). In the LFPs we find additive evoked response contributions in visual areas V2/4 but not in primary motor cortex A4, although visually triggered ERPs were also observed in area A4. MEG-SSVEFs were mainly created by additive evoked response contributions. Our results demonstrate that the identification of additive evoked response contributions is possible both in invasive and in non-invasive electrophysiological recordings.

Chiropractic manipulation of the neck can occasionally cause severe neurological complications, as demonstrated by this case report. A 59-year-old man who had previously sustained a cardiac infarction and a femoral-popliteal bypass operation, suffered from painful spasms of the cervical muscles for several weeks. After chiropractic manipulation, a left, predominantly brachiofacial, hemiparesis developed during the subsequent 24 hours. Computed tomography demonstrated a recent infarction in the area supplied by the ascending central and parietal branches of the right medial cerebral artery. Doppler sonography revealed occlusion of the right internal carotid artery as the cause. Marked improvement followed hypervolaemic haemodilution daily with 500 ml hydroxyethyl starch and intensive physiotherapy. Blood flow through the internal carotid artery was restored after seven days (demonstrated by Doppler ultrasound). In the presence of arteriosclerotic vessel changes particular care should be exercised in deciding on and execution of chiropractic manipulations.

Synchronous spike discharge of cortical neurons is thought to be a fingerprint of neuronal cooperativity. Because neighboring neurons are more densely connected to one another than neurons that are located further apart, near-synchronous spike discharge can be expected to be prevalent and it might provide an important basis for cortical computations. Using microelectrodes to record local groups of neurons does not allow for the reliable separation of synchronous spikes from different cells, because available spike sorting algorithms cannot correctly resolve the temporally overlapping waveforms. We show that high spike sorting performance of in vivo recordings, including overlapping spikes, can be achieved with a recently developed filter-based template matching procedure. Using tetrodes with a three-dimensional structure, we demonstrate with simulated data and ground truth in vitro data, obtained by dual intracellular recording of two neurons located next to a tetrode, that the spike sorting of synchronous spikes can be as successful as the spike sorting of nonoverlapping spikes and that the spatial information provided by multielectrodes greatly reduces the error rates. We apply the method to tetrode recordings from the prefrontal cortex of behaving primates, and we show that overlapping spikes can be identified and assigned to individual neurons to study synchronous activity in local groups of neurons.

Simultaneous measurements of intra-cortical electrophysiology and hemodynamic signals in primates are essential for relating human neuroimaging studies with intra-cortical electrophysiology in monkeys. Previously, technically challenging and resourcefully demanding techniques such as fMRI and intrinsic-signal optical imaging have been used for such studies. Functional near-infrared spectroscopy is a relatively less cumbersome neuroimaging method that uses near-infrared light to detect small changes in concentrations of oxy-hemoglobin (HbO), deoxy-hemoglobin (HbR) and total hemoglobin (HbT) in a volume of tissue with high specificity and temporal resolution. FNIRS is thus a good candidate for hemodynamic measurements in primates to acquire local hemodynamic signals during electrophysiological recordings. To test the feasibility of using epidural fNIRS with concomitant extracellular electrophysiology, we recorded neuronal and hemodynamic activity from the primary visual cortex of two anesthetized monkeys during visual stimulation. We recorded fNIRS epidurally, using one emitter and two detectors. We performed simultaneous cortical electrophysiology using tetrodes placed between the fNIRS sensors. We observed robust and reliable responses to the visual stimulation in both [HbO] and [HbR] signals, and quantified the signal-to-noise ratio of the epidurally measured signals. We also observed a positive correlation between stimulus-induced modulation of [HbO] and [HbR] signals and strength of neural modulation. Briefly, our results show that epidural fNIRS detects single-trial responses to visual stimuli on a trial-by-trial basis, and when coupled with cortical electrophysiology, is a promising tool for studying local hemodynamic signals and neurovascular coupling.

Simian tuberculosis is one of the most important bacterial diseases of non-human primates. Outbreaks of tuberculosis have been reported in primate colonies almost as long as these animals have been used experimentally or kept in zoological gardens. Significant progress has been made in reducing the incidence of tuberculosis in captive non-human primates, but despite reasonable precautions, outbreaks continue to occur. The most relevant reason is the high incidence of tuberculosis (TB) amongst the human population, in which tuberculosis is regarded as an important re-emerging disease. Furthermore, many non-human primate species originate from countries with a high burden of human TB. Therefore, Mycobacterium tuberculosis remains a significant threat in animals imported from countries with high rates of human infection. We report an outbreak of tuberculosis among a group of rhesus monkeys (Macaca mulatta) living in a closed, long-term colony. The outbreak coincided with reactivation of a TB infection in a co-worker who never had direct access to the animal house or laboratories. Eleven of 26 rhesus monkeys developed classical chronic active tuberculosis with typical caseous granulomata of varying size within different organs. The main organ system involved was the lung, suggesting an aerosol route of infection. Such an outbreak has significant economic consequences due to animal loss, disruption of research and costs related to disease control. Precautionary measures must be improved in order to avoid TB in non-human primate colonies.

Oscillatory neural activity in the gamma frequency range (>30 Hz) has been shown to accompany a wide variety of cognitive processes. So far, there has been limited success in assigning a unitary basic function to these oscillations, and critics have raised the argument that they could just be an epiphenomenon of neural processing. We propose a new framework that relates gamma oscillations observed in human, as well as in animal, experiments to two underlying processes: the comparison of memory contents with stimulus-related information and the utilization of signals derived from this comparison. This model attempts to explain early gamma-band responses in terms of the match between bottom-up and top-down information. Furthermore, it assumes that late gamma-band activity reflects the readout and utilization of the information resulting from this match.

Working memory (WM) capacity limitations and their neurophysiological correlates are of special relevance for the understanding of higher cognitive functions. Evidence from behavioral studies suggests that restricted attentional resources contribute to these capacity limitations. In an event-related functional magnetic resonance imaging (fMRI) study, we probed the capacity of the human visual WM system for up to four complex nonnatural objects using a delayed discrimination task. A number of prefrontal and parietal areas bilaterally showed increased blood oxygen level-dependent activity, relative to baseline, throughout the task when more than one object had to be held in memory. Monotonic increases in response to memory load were observed bilaterally in the dorsolateral prefrontal cortex (DLPFC) and the presupplementary motor area (pre-SMA). Conversely, activity in the frontal eye fields (FEFs) and in areas along the intraparietal sulcus (IPS) peaked when subjects had to maintain only two or three objects and decreased in the highest load condition. This dissociation of memory load effects on cortical activity suggests that the cognitive operations subserved by the IPS and FEF, which are most likely related to attention, fail to support visual WM when the capacity limit is approached. The correlation of brain activity with performance implies that only the operations performed by the DLPFC and pre-SMA, which support an integrated representation of visual information, helped subjects to maintain a reasonable level of performance in the highest load condition. These results indicate that at least two distinct cortical subsystems are recruited for visual WM, and that their interplay changes when the capacity limit is reached.

Oscillatory firing of neurons in response to visual stimuli has been observed to occur with different frequencies at multiple levels of the visual system. In the cat retina, oscillatory firing patterns occur with frequencies in the range of 60 to 120 Hz (omega-oscillations). These millisecond-precise temporal patterns are transmitted reliably to the cortex and may provide a feed-forward mechanism of response synchronization. In the cortex, visual responses often show oscillatory patterning with frequencies between 20 and 60 Hz (gamma-oscillations), which are not phase locked to the stimulus onset and therefore do not show up in regularly averaged evoked potentials. Gamma-oscillatory responses synchronize with millisecond precision over long distances and are mediated by the reciprocal corticocortical connectivity. Modulatory systems like the ascending reticular activating system facilitate synchronization and increase the strength of gamma-oscillations. During states of such functional cortical activation, the dominant frequency of the EEG is shifted from lower frequencies in the delta-/theta-range to higher frequencies in the gamma-range. Therefore, functional states indicate different degrees of temporal precision with which large neuronal populations interact. Response synchronization also depends on relations of global stimulus features. This suggests that millisecond-precise neuronal interactions serve as a fundamental mechanism for visual information processing.

Neuronal response synchronization with millisecond precision has been proposed to serve feature binding in vision and should therefore, like visual experience, depend on central states. Here we test this hypothesis by examining the occurrence and strength of response synchronization in areas 17 and 18 of anesthetized cats as a function of central states. These were assessed from the frequency content of the electroencephalogram, low power in the δ and high power in the γ frequency ranges (here 20–70 Hz) being considered as a signature of activated states. We evaluated both spontaneous state changes and transitions induced by electrical stimulation of the mesencephalic reticular formation. During states of low central activation, visual responses were robust but lacked signs of precise synchronization. At intermediate levels of activation, responses became synchronized and exhibited an oscillatory patterning in the range of 70–105 Hz. At higher levels of activation, a different pattern of response synchronization and oscillatory modulation appeared, oscillation frequency now being in the range of 20–65 Hz. The strength of response synchronization and oscillatory modulation in the 20–65 Hz range increased with further activation and was associated with a decrease in oscillation frequency. We propose that the oscillatory patterning in the 70–105 Hz range is attributable to oscillatory retinothalamic input and that a minimal level of activation is necessary for cortical neurons to follow this oscillatory pattern. In contrast, the synchronization of responses at oscillation frequencies in the 20–65 Hz range appears to result from intracortical synchronizing mechanisms, which become progressively more effective as central activation increases. Surprisingly, enhanced synchronization and oscillatory modulation in the γ frequency range were not associated with consistent increases in response amplitude, excluding a simple relation between central activation and neuronal discharge rate. The fact that intracortical synchronizing mechanisms are particularly effective during states of central activation supports the hypothesis that precise synchronization of responses plays a role in sensory processing.

The ease with which highly developed brains can generate representations of a virtually unlimited diversity of perceptual objects indicates that they have developed very efficient mechanisms to analyse and represent relations among incoming signals. Here, we propose that two complementary strategies are applied to cope with these combinatorial problems. First, elementary relations are represented by the tuned responses of individual neurons that acquire their specific response properties (feature selectivity) through appropriate convergence of input connections in hierarchically structured feed-forward architectures. Second, complex relations that cannot be represented economically by the responses of individual neurons are represented by assemblies of cells that are generated by dynamic association of individual, featureselective cells. The signature identifying the responses of an assembly as components of a coherent code is thought to be the synchronicity of the respective discharges. The compatibility of this hypothesis is examined in the context of recent data on the dynamics of synchronization phenomena, the dependence of synchronization on central states and the relations between the synchronization behaviour of neurons and perception.

1. To understand the structural basis of the different types of interhemispheric synchronizations described in the preceding paper, we made sections of the corpus callosum and lesions of extrastriate cortex. We measured the effects of such operations on the frequency of encounter, width and strength of T, C, and H peaks in cross-correlation histograms computed from single-unit and multiunit recordings from areas 17-18 of opposite cortical hemispheres in the cat. 2. Sectioning of the corpus callosum led to a complete abolition of T and C couplings and a strong reduction of encounter rate and strength of H coupling. A section limited to the posterior half of the corpus callosum abolished T and C couplings completely. This suggests that T and C couplings are mediated by the direct reciprocal connections between visual cortical areas circulating through the posterior part of the corpus callosum. 3. The encounter rate of H peaks depended on the extent of the callosal cut. Larger lesions gave a more pronounced reduction of the number of H peaks. From this observation we conclude that H peaks are at least partially mediated by polysynaptic pathways involving widely distributed cortical regions. 4. Extensive lesions of extrastriate cortex were made by aspiration of the gray matter or injections of ibotenic acid. These lesions removed the direct inputs from cortical areas sending ipsilateral as well as contralateral inputs to the area 17-18 border region. Encounter rate and coupling strength of C and H peaks were decreased, whereas little effect was observed on T peaks. 5. These results demonstrate that all types of interhemispheric synchronization are mediated by corticocortical connections and that T and C peaks are generated by reciprocal connections between areas 17 and 18 of each hemisphere. Feedback connections play a role in mediating or facilitating the C and H types of interhemispheric synchronization.

Cytochrome oxidase bands in area V2 of the primate visual cortex constitute separate relays for parallel channels relaying information from area V1 to other extrastriate cortical areas. We investigated whether information is transferred at the same speed in the different channels by measuring the latencies of neurons in different cytochrome oxidase bands identified by the presence or absence of retrogradely labeled cells from injections in area V4. Results show that neurons in the thick and pale bands respond 20 msec earlier than those in the thin bands. We also found that color-selective neurons respond later than neurons with no selectivity for color and that direction-selective neurons have shorter latencies than neurons with no selectivity for the direction of stimulus movement.

1982 postulierten Leslie Ungerleider und Mortimer Mishkin zwei anatomisch unterschiedliche und funktionell spezialisierte kortikale Projektionssysteme zur Verarbeitung visueller Eindrucke, die im primaren visuellen Kortex (Area striata, BA17, auch V1 genannt) des Okzipitallappens ihren Ursprung nehmen: ein dorsales okzipitoparietales Projektionssystem, das sich uber die visuellen Assoziationsareale des Parietallappens erstreckt, und ein ventrales okzipitotemporales, das die visuellen Areale des Temporallappens einbezieht. Beide Projektionssysteme unterhalten wechselseitige Verbindungen mit einer Reihe limbischer Strukturen und dem prafrontalen Kortex, wo Information von verschiedenen Sinnesmodalitaten integriert wird.

International audience; The present work investigates instantaneous synchronization in multivariate signals. It introduces a new method to detect subsets of synchronized time series that do not consider any baseline information. The method is based on a Bayesian Gaussian mixture model applied at each location of a time-frequency map. The work assesses the relevance of detected subsets by a stability measure. The application to Local Field Potentials measured during a visuo-motor experiment in monkeys reveals a subset of synchronized time series measured in the visual cortex.

Precise temporal synchrony of spike firing has been postulated as an important neuronal mechanism for signal integration and the induction of plasticity in neocortex. As prefrontal cortex plays an important role in organizing memory and executive functions, the convergence of multiple visual pathways onto PFC predicts that neurons should preferentially synchronize their spiking when stimulus information is processed. Furthermore, synchronous spike firing should intensify if memory processes require the induction of neuronal plasticity, even if this is only for short-term. Here we show with multiple simultaneously recorded units in ventral prefrontal cortex that neurons participate in 3 ms precise synchronous discharges distributed across multiple sites separated by at least 500 µm. The frequency of synchronous firing is modulated by behavioral performance and is specific for the memorized visual stimuli. In particular, during the memory period in which activity is not stimulus driven, larger groups of up to 7 sites exhibit performance dependent modulation of their spike synchronization.

Simultaneous spike-counts of neural populations are typically modeled by a Gaussian distribution. On short time scales, however, this distribution is too restrictive to describe and analyze multivariate distributions of discrete spike-counts. We present an alternative that is based on copulas and can account for arbitrary marginal distributions, including Poisson and negative binomial distributions as well as second and higher-order interactions. We describe maximum likelihood-based procedures for fitting copula-based models to spike-count data, and we derive a so-called flashlight transformation which makes it possible to move the tail dependence of an arbitrary copula into an arbitrary orthant of the multivariate probability distribution. Mixtures of copulas that combine different dependence structures and thereby model different driving processes simultaneously are also introduced. First, we apply copula-based models to populations of integrate-and-fire neurons receiving partially correlated input and show that the best fitting copulas provide information about the functional connectivity of coupled neurons which can be extracted using the flashlight transformation. We then apply the new method to data which were recorded from macaque prefrontal cortex using a multi-tetrode array. We find that copula-based distributions with negative binomial marginals provide an appropriate stochastic model for the multivariate spike-count distributions rather than the multivariate Poisson latent variables distribution and the often used multivariate normal distribution. The dependence structure of these distributions provides evidence for common inhibitory input to all recorded stimulus encoding neurons. Finally, we show that copula-based models can be successfully used to evaluate neural codes, e.g., to characterize stimulus-dependent spike-count distributions with information measures. This demonstrates that copula-based models are not only a versatile class of models for multivariate distributions of spike-counts, but that those models can be exploited to understand functional dependencies., Author Summary The brain has an enormous number of neurons that do not work alone but in an ensemble. Yet, mostly individual neurons were measured in the past and therefore models were restricted to independent neurons. With the advent of new multi-electrode techniques, however, it becomes possible to measure a great number of neurons simultaneously. As a result, models of how populations of neurons co-vary are becoming increasingly important. Here, we describe such a framework based on so-called copulas. Copulas allow to separate the neural variation structure of the population from the variability of the individual neurons. Contrary to standard models, versatile dependence structures can be described using this approach. We explore what additional information is provided by the detailed dependence. For simulated neurons, we show that the variation structure of the population allows inference of the underlying connectivity structure of the neurons. The power of the approach is demonstrated on a memory experiment in macaque monkey. We show that our framework describes the measurements better than the standard models and identify possible network connections of the measured neurons.

We present a method which allows for the blind source separation of sparse overcomplete mixtures. In this method, linear filters are used to find a new representation of the data and to enhance the signal-to-noise ratio. Further, "Deconfusion", a method similar to the independent component analysis, decorrelates the filter outputs. In particular, the method was developed to extract neural activity signals from extracellular recordings. In this sense, the method can be viewed as a combined spike detection and classification algorithm. We compare the performance of our method to those of existing spike sorting algorithms, and also apply it to recordings from real experiments with macaque monkeys.

Neuronal processing of sensory information requires that rapidly changing synaptic inputs are continuously transformed into action potentials. Variability of spike firing is generally considered as noise and might therefore interfere with the reliability of synaptic transmission in sensory systems. In a system in which the number of spikes is a variable that determines the quality of neuronal transmission, variability of spike counts is a paradoxical attribute. In contrast, in a system in which precisely correlated spike firing can influence synaptic integration, response variability might be used as an additional mechanism for coding information. As acetylcholine has been shown to reduce spike-frequency adaptation and enhance gamma frequency (21–70 Hz) oscillations, we set out to study the influence of cholinergic modulation on the variability of spike counts and gamma oscillations. Iontophoretic application of carbachol, a cholinergic agonist, in cat primary visual cortex or electrical stimulation of the mesencephalic reticular formation reduced the spike count variability and stabilized gamma frequency oscillations of visually induced responses. Response stabilization was correlated with enhancement of gamma-frequency oscillations but not with averaged firing rates. Lowering variability of sensory responses might be a mechanism to stabilize and improve reliability of neuronal transmission. Cholinergic activation may therefore influence the efficacy of neuronal transmission by modulating the precise timing of neuronal responses.

Short-term memory requires the coordination of sub-processes like encoding, retention, retrieval and comparison of stored material to subsequent input. Neuronal oscillations have an inherent time structure, can effectively coordinate synaptic integration of large neuron populations and could therefore organize and integrate distributed sub-processes in time and space. We observed field potential oscillations (14–95 Hz) in ventral prefrontal cortex of monkeys performing a visual memory task. Stimulus-selective and performance-dependent oscillations occurred simultaneously at 65–95 Hz and 14–50 Hz, the latter being phase-locked throughout memory maintenance. We propose that prefrontal oscillatory activity may be instrumental for the dynamical integration of local and global neuronal processes underlying short-term memory.

Poster presentation: Self-organized critical (SOC) systems are complex dynamical systems that may express cascades of events, called avalanches [1]. The SOC state was proposed to govern brain function, because of its activity fluctuations over many orders of magnitude, its sensitivity to small input and its long term stability [2,3]. In addition, the critical state is optimal for information storage and processing [4]. Both hallmark features of SOC systems, a power law distribution f(s) for the avalanche size s and a branching parameter (bp) of unity, were found for neuronal avalanches recorded in vitro [5]. However, recordings in vivo yielded contradictory results [6]. Electrophysiological recordings in vivo only cover a small fraction of the brain, while criticality analysis assumes that the complete system is sampled. We hypothesized that spatial subsampling might influence the observed avalanche statistics. In addition, SOC models can have different connectivity, but always show a power law for f(s) and bp = 1 when fully sampled. This may not be the case under subsampling, however. Here, we wanted to know whether a state change from awake to asleep could be modeled by changing the connectivity of a SOC model without leaving the critical state. We simulated a SOC model [1] and calculated f(s) and bp obtained from sampling only the activity of a set of 4 × 4 sites, representing the electrode positions in the cortex. We compared these results with results obtained from multielectrode recordings of local field potentials (LFP) in the cortex of behaving monkeys. We calculated f(s) and bp for the LFP activity recorded while the monkey was either awake or asleep and compared these results to results obtained from two subsampled SOC model with different connectivity. f(s) and bp were very similar for both the experiments and the subsampled SOC model, but in contrast to the fully sampled model, f(s) did not show a power law and bp was smaller than unity. With increasing the distance between the sampling sites, f(s) changed from "apparently supercritical" to "apparently subcritical" distributions in both the model and the LFP data. f(s) and bp calculated from LFP recorded during awake and asleep differed. These changes could be explained by altering the connectivity in the SOC model. Our results show that subsampling can prevent the observation of the characteristic power law and bp in SOC systems, and misclassifications of critical systems as sub- or supercritical are possible. In addition, a change in f(s) and bp for different states (awake/asleep) does not necessarily imply a change from criticality to sub- or supercriticality, but can also be explained by a change in the effective connectivity of the network without leaving the critical state.

Poster presentation: The analysis of neuronal processes distributed across multiple cortical areas aims at the identification of interactions between signals recorded at different sites. Such interactions can be described by measuring the stability of phase angles in the case of oscillatory signals or other forms of signal dependencies for less regular signals. Before, however, any form of interaction can be analyzed at a given time and frequency, it is necessary to assess whether all potentially contributing signals are present. We have developed a new statistical procedure for the detection of coincident power in multiple simultaneously recorded analog signals, allowing the classification of events as 'non-accidental co-activation'. This method can effectively operate on single trials, each lasting only for a few seconds. Signals need to be transformed into time-frequency space, e.g. by applying a short-time Fourier transformation using a Gaussian window. The discrete wavelet transform (DWT) is used in order to weight the resulting power patterns according to their frequency. Subsequently, the weighted power patterns are binarized via applying a threshold. At this final stage, significant power coincidence is determined across all subgroups of channel combinations for individual frequencies by selecting the maximum ratio between observed and expected duration of co-activation as test statistic. The null hypothesis that the activity in each channel is independent from the activity in every other channel is simulated by independent, random rotation of the respective activity patterns. We applied this procedure to single trials of multiple simultaneously sampled local field potentials (LFPs) obtained from occipital, parietal, central and precentral areas of three macaque monkeys. Since their task was to use visual cues to perform a precise arm movement, co-activation of numerous cortical sites was expected. In a data set with 17 channels analyzed, up to 13 sites expressed simultaneous power in the range between 5 and 240 Hz. On average, more than 50% of active channels participated at least once in a significant power co-activation pattern (PCP). Because the significance of such PCPs can be evaluated at the level of single trials, we are confident that this procedure is useful to study single trial variability with sufficient accuracy that much of the behavioral variability can be explained by the dynamics of the underlying distributed neuronal processes.