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Logothetis, N. K.

Publications and source records attributed to Logothetis, N. K..

14 recordsLinked to original sources

Mouse primary visual cortex neurons respond to the illusory ''darker than black'' in neon color spreading.

Illusions are a powerful tool for studying the single neuron correlates of perception. Here, we introduce the neon color spreading (NCS) illusion in mice and report the neuronal correlates of illusory brightness, which has heretofore only been studied using human fMRI. We designed a novel NCS paradigm to evoke the percept of an illusory drifting grating and analyzed the activity of 520 single units in the mouse primary visual cortex (V1). A substantial proportion of V1 single units (60.5%) responded to illusory gratings with direction tuning matched to their preferred direction, which was determined using physically presented luminance-defined gratings (LDG). Moreover, by presenting LDG gratings with a 180{degrees} phase shift relative to NCs gratings, we show that spatial phase tuning shifted 180{degrees} for most single units. This finding conclusively demonstrates that V1 single units respond to illusory brightness. Using this novel mouse paradigm, we show that responses to illusory gratings have a lower magnitude and are delayed relative to physical gratings. We determined where V1 single units fell in the V1 cellular hierarchy (based on their susceptibility to surround suppression, their putative classification as interneuron or pyramidal neuron, and designation as a simple or complex cell) and found that higher-level V1 single units are more responsive to NCS stimuli. These findings resolve the debate of whether V1 is involved in illusory brightness processing and reveal a V1 hierarchical organization in which higher-level neurons are pivotal to the processing of illusory qualities, such as brightness.

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Focusing perceptual attention in one modality constrains subsequent learning in another modality

Contemporary neuroscience and psychiatry suggest that attention to decision outcomes guides rule learning by adjusting stimulus-outcome associations. Separately, sensory neurophysiology conceptualizes attention as a filter that improves perception. Here, we show that the contemporary view is incomplete by demonstrating an unconventional and novel effect of perceptual attention on subsequent outcome-based rule learning. Moreover, we show for the first time in rodents that, like in primates, this attentional process involves tuning of modality specific cortico-cortical interactions. We designed a novel head-fixed rat-on-a-treadmill apparatus and used it to train rats to discriminate auditory-visual stimuli using one modality and then reduced stimulus discriminability in that modality. We observed perceptual learning suggesting engagement of perceptual attention. Moreover, engaging visual perceptual attention resulted in more saccades and increased frontal-visual cortex EEG Granger causality relative to engaging auditory perceptual attention. We then presented novel and easily discriminable stimuli in both modalities and measured outcome-driven learning in the other modality. Learning was slower after engaging perceptual attention. Our work suggests that a more complete description of learning requires integrating these previously siloed concepts of attention. Moreover, treating impaired set-shifting as a trans-diagnostic symptom may require targeting different neural circuits for perceptual attention or outcome-based attention depending on which type of attention is impaired in each neuro-psychiatric disorder.

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A model of Ponto-Geniculo-Occipital waves supports bidirectional control of cortical plasticity across sleep-stages

During sleep, cortical network connectivity likely undergoes both synaptic potentiation and depression through system consolidation and homeostatic processes. However, how these modifications are coordinated across sleep stages remains largely unknown. Candidate mechanisms are Ponto-Geniculo-Occipital (PGO) waves, propagating across several structures during Rapid Eye Movement (REM) sleep and the transitional stage from non-REM sleep to REM sleep (pre-REM), and exhibiting sleep stage-specific dynamic patterns. To understand their impact on cortical plasticity, we built an acetylcholine-modulated neural mass model of PGO wave propagation through pons, thalamus and cortex, reproducing a broad range of electrophysiological characteristics across sleep stages. Using a population model of Spike-Time-Dependent Plasticity, we show that cortical circuits undergo different transient regimes depending on the sleep stage, with different impacts on plasticity. Specifically, PGO-induced recurrent cortical activities lead to the potentiation of cortico-cortical synapses during pre-REM, and to their depression during REM sleep. Overall, these results shed light on how the dynamical properties of sleep events propagating to cortical circuits can favor different types of local plastic changes. The variety of events occurring across sleep stages may thus be instrumental in controlling the reorganization of cortical networks from one day to the next. Significance statementConsiderable evidence supports rescaling of cortical synaptic connec-tions during sleep, requiring both long term potentiation to consolidate newly acquired memories, and long-term depression to maintain homeostatic levels of brain activity. However, which aspects of sleep activity contribute to this bidirectional control of plasticity remains unclear. This computational modeling study suggests that widespread transient phenomena called Ponto-geniculo-occipital (PGO) waves, have a sleep-stage dependent effect on plasticity. The alternation between sleep stages can thus be exploited in combination with spontaneously occurring transients, to trigger both up- and down-regulating effects on cortical connectivity, and may explain why the basic structure of sleep-cycles is a well-preserved property across mammalian species.

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Uncovering the Organization of Neural Circuits with Generalized Phase Locking Analysis

Despite the considerable progress of in vivo neural recording techniques, inferring the biophysical mechanisms underlying large scale coordination of brain activity from neural data remains challenging. One obstacle is the difficulty to link high dimensional functional connectivity measures to mechanistic models of network activity. We address this issue by investigating spike-field coupling (SFC) measurements, which quantify the synchronization between, on the one hand, the action potentials produced by neurons, and on the other hand a mesoscopic "field" signals, reflecting subthreshold activities at possibly multiple recording sites. As the number of recording sites gets large, the amount of pairwise SFC measurements becomes overwhelmingly challenging to interpret. We develop Generalized Phase Locking Analysis (GPLA) as a dimensionality reduction of this multivariate SFC. GPLA describes the dominant coupling between field activity and neural ensembles across space and frequencies, thereby providing rich yet interpretable information. In particular, we show that GPLA features are biophysically interpretable when used in conjunction with appropriate network models, such that we can identify the influence of underlying circuit properties on these features. We demonstrate the statistical benefits and interpretability of this approach in various computational models and Utah array recordings. The results suggest that GPLA used jointly with biophysical modeling can help uncover the contribution of recurrent microcircuits to the spatio-temporal dynamics observed in multi-channel experimental recordings.

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Connection Stripes in the Primate Insula

The insula has been classically divided into vast granular, dysgranular and agranular sectors. Over the years, several distinct studies proposed subdivisions of these sectors, with however no consensus. We recently proposed a cyto- and myelo-architectonic partition in which each sector contained sharply delimited areas (Evrard et al. 2014 J Comp Neurol 522: 64-97). Some of these areas were further divided into distinct subareas with obvious functional implications. Here, we examined the spatial relationship between architectonic boundaries and tract-tracing labeling in the insula in the macaque monkey. Injections of neuronal tracers in distinct areas of the prefrontal or anterior cingulate cortices produced heterogeneous and discontinuous patterns of anterograde and retrograde labeling in the insula. These patterns were made of sharply delimited patches forming anteroposterior stripes across consecutive coronal sections. While the overall pattern of labeling varied with the injection site, the patches systematically coincided with specific architectonic subareas, particularly in the dysgranular insula. This unequivocally validates our prior architectonic partition and strongly supports the idea of a refined modular Bauplan of the primate insula. This modular organization may underlie a serial stream of integration of interoception with self-agency and social activities across distinct insulo-prefrontal processing units that need to be explored.

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Subcortical Atlas of the Rhesus Macaque (SARM) for Magnetic Resonance Imaging

Digitized neuroanatomical atlases are crucial for localizing brain structures and analyzing functional networks identified by magnetic resonance imaging (MRI). To aid in MRI data analysis, we have created a comprehensive parcellation of the rhesus macaque subcortex using a high-resolution ex vivo structural imaging scan. The structural scan and its parcellation were warped to the updated NIMH Macaque Template (NMT v2), an in vivo population template, where the parcellation was refined to produce the Subcortical Atlas of the Rhesus Macaque (SARM). The subcortical parcellation and nomenclature reflect those of the 4th edition of the Rhesus Monkey Brain in Stereotaxic Coordinates (RMBSC4; Paxinos et al., in preparation). The SARM features six parcellation levels, arranged hierarchically from fine regions-of-interest (ROIs) to broader composite regions, suited for fMRI studies. As a test, we ran a functional localizer for the dorsal lateral geniculate (DLG) nucleus in three macaques and found significant fMRI activation in this atlas region. The SARM has been made openly available to the neuroimaging community and can easily be used with common MR data processing software, such as AFNI, where the atlas can be embedded into the software alongside cortical macaque atlases. HighlightsO_LIWe present the Subcortical Atlas of the Rhesus Macaque (SARM). C_LIO_LISARM provides a neuroanatomical reference frame for neuroimaging analysis. C_LIO_LIThe entire subcortex is mapped, including the thalamus, basal ganglia, and brainstem. C_LIO_LIROIs are grouped hierarchically, making SARM useful at multiple spatial resolutions. C_LIO_LISARM is in the NMT v2 template space and complements the CHARM atlas for the cortex. C_LI

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Synchronous spiking associated with high gamma oscillations in prefrontal cortex exerts top-down control over a 5Hz-rhythmic modulation of spiking in locus coeruleus

The brainstem noradrenergic locus coeruleus (LC) is reciprocally connected with the prefrontal cortex (PFC). Strong coupling between LC spiking and depolarizing phase of slow (1 - 2 Hz) waves in the PFC field potentials during sleep and anesthesia suggests that the LC drives cortical state transition. Reciprocal LC-PFC connectivity should also allow interactions in the opposing (top-down) direction, but prior work has only studied prefrontal control over LC activity using direct electrical (or optogenetic) stimulation paradigms. Here, we describe the physiological characteristics of naturally occurring top-down prefrontal-coerulear interactions. Specifically, we recorded LC multi-unit activity (MUA) simultaneously with PFC single unit and local field potential (LFP) activity in urethane-anesthetized rats. We observed cross-regional coupling between the phase of ~5 Hz oscillations in LC population spike rate and the power of PFC LFP oscillations within the high Gamma (hGamma) range (60 - 200 Hz). Specifically, transient increases in PFC hGamma power preceded peaks in the ~5 Hz LC-MUA oscillation. Analysis of cross-regional transfer entropy demonstrated that the PFC hGamma transients were predictive of a transient increase in LC-MUA. A ~29 msec delay between these signals was consistent with the conduction velocity from the PFC to the LC. Finally, we showed that PFC hGamma transients are associated with synchronized spiking of a subset (27%) of PFC single units. Our data suggest that, PFC hGamma transients may indicate the timing of the top-down excitatory input to LC, at least under conditions when LC neuronal population activity fluctuates rhythmically at ~5 Hz. Synchronized PFC neuronal spiking that occurs during hGamma transients may provide a previously unknown mode of top-down control over the LC.

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Noradrenergic locus coeruleus ensembles evoke different states in rat prefrontal cortex

The noradrenergic locus coeruleus (LC) is a crucial controller of brain and behavioral states. Activating LC neurons synchronously en masse by electrical or optogenetic stimulation promotes a stereotypical "activated" high-frequency cortical state. However, it has been recently reported that spontaneous LC cell-pairs have sparse yet structured time-averaged cross-correlations, which is unlike the high synchrony of en masse neuronal stimulation. This suggests the untested possibility that LC population activity may be made of distinct multi-cell ensembles each with unique temporal evolution of activity. We used non-negative matrix factorization (NMF) to analyze large populations of LC single units simultaneously recorded in the rat LC. Synthetic spike train simulations showed that NMF, unlike the traditional time-averaged pairwise correlations, detects both the precise neuronal composition and the activation time courses of each ensemble. NMF identified the existence of robust ensembles of spontaneously co-active LC neurons. Since LC neurons selectively project to specific forebrain regions, we hypothesized that individual LC ensembles produce different cortical states. To test this hypothesis, we triggered local field potentials (LFP) in cortical area 24a on the activation of distinct LC ensembles. We found four cortical states, each with different spectro-temporal LFP characteristics, that were robust across sessions and animals. While some LC ensembles triggered the activated state, others were associated with a beta oscillation-specific state or a reduced high frequency oscillation state. Thus - in contrast to the stereotypical "activated" brain state evoked by en masse LC stimulation - spontaneous activation of distinct LC ensembles can control a multitude of cortical states.

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Prefrontal state fluctuations control access to consciousness

Access of sensory information to consciousness is thought to be mediated through ignition of neural activity in the prefrontal cortex (PFC). Ignition occurs once activity elicited by sensory input crosses a threshold, which has been shown to depend on brain state fluctuations. However, the neural correlates of fluctuations and their interaction with the neural representations of conscious contents within the PFC remain largely unknown. To understand the role of prefrontal state fluctuations in conscious access, we combined multielectrode intracortical recordings with a no-report binocular rivalry (BR) paradigm that induces spontaneously-driven changes in conscious perception. During BR, antagonistic coupling of two prefrontal states, characterised by dominance of low frequency (1-9Hz) or beta (20-40Hz) local field potentials (LFP), reflect competition between two states of visual consciousness; perceptual update and stability, respectively. Low frequency perisynaptic bursts precede spontaneous transitions in conscious perception, signalling upcoming perceptual update of conscious content. We therefore show that it is a global cortical state that seems to drive internal switches, rather than the spiking activity of selective neuronal ensembles, which subsequently, only report the active percept. Beta band bursts were found to be correlated with periods of stable conscious perception, and selectively synchronised the neural ensemble coding for the consciously perceived stimulus. Similar ongoing fluctuations in the LFPs, with dynamics resembling the distribution of perceptual dominance periods during BR, dominated the prefrontal cortex during resting-state, thus pointing to their default, endogenous nature. Our results suggest that the two modes of conscious perception: perceptual update, and stability, can be associated with distinct prefrontal cortical states.

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Decoding the contents of consciousness from prefrontal ensembles

Multiple theories attribute to the primate prefrontal cortex a critical role in conscious perception. However, opposing views caution that prefrontal activity could reflect other cognitive variables during paradigms investigating consciousness, such as decision-making, monitoring and motor reports. To resolve this ongoing debate, we recorded from prefrontal ensembles of macaque monkeys during a no-report paradigm of binocular rivalry that instigates internally driven transitions in conscious perception. We could decode the contents of consciousness from prefrontal ensemble activity during binocular rivalry with an accuracy similar to when these stimuli were presented without competition. Oculomotor signals, used to infer conscious content, were not the only source of these representations since visual input could be significantly decoded when eye movements were suppressed. Our results suggest that the collective dynamics of prefrontal cortex populations reflect internally generated changes in the content of consciousness during multistable perception. One sentence summaryNeural correlates of conscious perception can be detected and perceptual contents can be reliably decoded from the spiking activity of prefrontal populations.

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Measuring single neuron visual receptive field sizes by fMRI

The non-invasive measurements of neuronal receptive field (RF) properties in-vivo allow a detailed understanding of brain organization as well as its plasticity by longitudinal following of potential changes. Visual RFs measured invasively by electrophysiology in animal models have traditionally provided a great extent of our current knowledge about the visual brain and its disorders. Voxel based estimates of population RF (pRF) by functional magnetic resonance imaging (fMRI) in humans revolutionized the field and have been used extensively in numerous studies. However, current methods cannot estimate single-neuron RF sizes as they reflect large populations of neurons with individual RF scatter. Here, we introduce a new approach to estimate RF size using spatial frequency selectivity to checkerboard patterns. This method allowed us to obtain non-invasive, single-unit, RF estimates in human V1 for the first time. These estimates were significantly smaller compared to prior pRF methods. Further, fMRI and electrophysiological experiments in non-human primates demonstrated an exceptional match validating the approach.

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Organization of Area hV5/MT+ in Subjects with Homonymous Visual Field Defects

Damage to the primary visual cortex (V1) leads to a visual field loss (scotoma) in the retinotopically corresponding part of the visual field. Nonetheless, a small amount of residual visual sensitivity persists within the blind field. This residual capacity has been linked to activity observed in the middle temporal area complex (V5/MT+). However, it remains unknown whether the organization of hV5/MT+ changes following V1 lesions. We studied the organization of area hV5/MT+ of five patients with dense homonymous defects in a quadrant of the visual field as a result of partial V1+ or optic radiation lesions. To do so, we developed a new method, which models the boundaries of population receptive fields directly from the BOLD signal of each voxel in the visual cortex. We found responses in hV5/MT+ arising inside the scotoma for all patients and identified two possible sources of activation: 1) responses might originate from partially lesioned parts of area V1 corresponding to the scotoma, and 2) responses can also originate independent of area V1 input suggesting the existence of functional V1-bypassing pathways. Apparently, visually driven activity observed in hV5/MT+ is not sufficient to mediate conscious vision. More surprisingly, visually driven activity in corresponding regions of V1 and early extrastriate areas including hV5/MT+ did not guarantee visual perception in the group of patients with post-geniculate lesions that we examined. This suggests that the fine coordination of visual activity patterns across visual areas may be an important determinant of whether visual perception persists following visual cortical lesions.

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Non-monotonic spatial structure of interneuronal correlations in prefrontal microcircuits

Correlated fluctuations of single neuron discharges, on a mesoscopic scale, decrease as a function of lateral distance in early sensory cortices, reflecting a rapid spatial decay of lateral connection probability and excitation. However, spatial periodicities in horizontal connectivity and associational input as well as an enhanced probability of lateral excitatory connections in the association cortex could theoretically result in non-monotonic correlation structures. Here we show such a spatially non-monotonic correlation structure, characterized by significantly positive long-range correlations, in the inferior convexity of the macaque prefrontal cortex. This functional connectivity kernel was more pronounced during wakefulness than anesthesia and could be largely attributed to the spatial pattern of correlated variability between functionally similar neurons during structured visual stimulation. These results suggest that the spatial decay of lateral functional connectivity is not a common organizational principle of neocortical microcircuits. A non-monotonic correlation structure could reflect a critical topological feature of prefrontal microcircuits, facilitating their role in integrative processes.\n\nSignificance statementThe spatial structure of correlated activity of neurons in lower-order visual areas has been shown to linearly decrease as a measure of distance. The shape of correlated variability is a defining feature of cortical microcircuits as it constrains the computational power and diversity of a region. We show here for the first time a non-monotonic spatial structure of functional connectivity in the pre-frontal cortex where distal interactions are just as strong as proximal interactions during visual engagement of functionally similar PFC neurons. Such a nonmonotonic structure of functional connectivity could have far-reaching consequences in rethinking the nature and the role of prefrontal microcircuits in various cognitive states.

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Monitoring large populations of locus coeruleus neurons reveals the non-global nature of the norepinephrine neuromodulatory system

Understanding the forebrain neuromodulation by the noradrenergic locus coeruleus (LC) is fundamental for cognitive and systems neuroscience. The diffuse projections of individual LC neurons and presumably their synchronous spiking have long been perceived as features of the global nature of noradrenergic neuromodulation. Yet, the commonly referenced \"synchrony\" underlying global neuromodulation, has never been assessed in a large population, nor has it been related to projection target specificity. Here, we recorded up to 52 single units simultaneously (3164 unit pairs in total) in rat LC and characterized projections by stimulating 15 forebrain sites. Spike count correlations were low and, surprisingly, only 13% of pairwise spike trains had synchronized spontaneous discharge. Notably, even noxious sensory stimulation did not activate the entire population, only evoking synchronized responses in ~16% of units on each trial. We also identified novel infra-slow (0.01-1 Hz) fluctuations of LC unit spiking that were asynchronous across the population. A minority, synchronized possibly by gap junctions, was biased toward restricted (non-global) forebrain projection patterns. Finally, we characterized two types of LC single units differing by waveform shape, propensity for synchronization, and interactions with cortex. These cell types formed finely-structured ensembles. Our findings suggest that the LC conveys a highly complex, differentiated, and potentially target-specific neuromodulatory signal.

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