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Fries, P.

Publications and source records attributed to Fries, P..

At least 37 records · Page 2Linked to original sources

Phase leads between oscillatory visual stimuli induce a salience illusion

Neuronal populations often engage in oscillations, and corresponding theories and computational models propose that this affects their impact on other neurons. Specifically, when two neuronal populations oscillating at similar frequencies compete for impact, the phase-leading one might have an advantage by providing inputs to target neurons earlier. Here, we provide direct empirical support by driving visual neuronal responses with oscillating stimuli. We superimposed two orthogonal grating stimuli of temporally oscillating intensities, whose phase relations were precisely controlled. The leading stimulus was perceived as oscillating more intensely. This held for phase leads of a few milliseconds, and for each participant and almost every trial. Thus, we found a strong perceptual illusion directly predicted by theories on the functional role of oscillations for neuronal interactions.

neuroscience↗

Perplexity about periodicity repeats perpetually: A response to Brookshire

Brookshire (2022) claims that previous analyses of periodicity in detection performance after a reset event suffer from extreme false-positive rates. Here we show that this conclusion is based on an incorrect implemention of a null-hypothesis of aperiodicity, and that a correct implementation confirms low false-positive rates. Furthermore, we clarify that the previously used method of shuffling-in-time, and thereby shuffling-in-phase, cleanly implements the null hypothesis of no temporal structure after the reset, and thereby of no phase locking to the reset. Moving from a corresponding phase-locking spectrum to an inference on the periodicity of the underlying process can be accomplished by parameterizing the spectrum. This can separate periodic from non-periodic components, and quantify the strength of periodicity.

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Quantifying rhythmicity in perceptual reports

Several recent studies investigated the rhythmic nature of cognitive processes that lead to perception and behavioral report. These studies used different methods, and there has not yet been an agreement on a general standard. Here, we present a way to test and quantitatively compare these methods. We simulated behavioral data from a typical experiment and analyzed these data with several methods. We applied the main methods found in the literature, namely sine-wave fitting, the Discrete Fourier Transform (DFT) and the Least Square Spectrum (LSS). DFT and LSS can be applied both on the averaged accuracy time course and on single trials. LSS is mathematically equivalent to DFT in the case of regular, but not irregular sampling - which is more common. LSS additionally offers the possibility to take into account a weighting factor which affects the strength of the rhythm, such as arousal. Statistical inferences were done either on the investigated sample (fixed-effect) or on the population (random-effect) of simulated participants. Multiple comparisons across frequencies were corrected using False-Discovery-Rate, Bonferroni, or the Max-Based approach. To perform a quantitative comparison, we calculated Sensitivity, Specificity and D-prime of the investigated analysis methods and statistical approaches. Within the investigated parameter range, single-trial methods had higher sensitivity and D-prime than the methods based on the averaged-accuracy-time-course. This effect was further increased for a simulated rhythm of higher frequency. If an additional (observable) factor influenced detection performance, adding this factor as weight in the LSS further improved Sensitivity and D-prime. For multiple comparison correction, the Max-Based approach provided the highest Specificity and D-prime, closely followed by the Bonferroni approach. Given a fixed total amount of trials, the random-effect approach had higher D-prime when trials were distributed over a larger number of participants, even though this gave less trials per participant. Finally, we present the idea of using a dampened sinusoidal oscillator instead of a simple sinusoidal function, to further improve the fit to behavioral rhythmicity observed after a reset event.

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Selective V1-to-V4 communication of attended stimuli mediated by attentional effects in V1

Selective attention implements preferential routing of attended stimuli, likely through increasing the influence of the respective synaptic inputs on higher-area neurons. As the inputs of competing stimuli converge onto postsynaptic neurons, presynaptic circuits might offer the best target for attentional top-down influences. If those influences enabled presynaptic circuits to selectively entrain postsynaptic neurons, this might explain selective routing. Indeed, when two visual stimuli induce two gamma rhythms in V1, only the gamma induced by the attended stimulus entrains gamma in V4. Here, we modeled induced responses with a Dynamic Causal Model for Cross-Spectral Densities and found that selective entrainment can be explained by attentional modulation of intrinsic V1 connections. Specifically, local inhibition was decreased in the granular input layer and increased in the supragranular output layer of the V1 circuit that processed the attended stimulus. Thus, presynaptic attentional influences and ensuing entrainment were sufficient to mediate selective routing. HIGHLIGHTSO_LIWe model selective visual attention in macaques using Dynamic Causal Modeling. C_LIO_LIIntrinsic V1 modulation can explain attention effects in V1-V4 communication. C_LIO_LIModulation of superficial and granular inhibition is key to induce the effects. C_LIO_LIThose modulations increase V1-V4 communication in a feedforward manner. C_LI GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/484223v2_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@1cc79a7org.highwire.dtl.DTLVardef@146e6bdorg.highwire.dtl.DTLVardef@1d6bd6borg.highwire.dtl.DTLVardef@12dd663_HPS_FORMAT_FIGEXP M_FIG C_FIG

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Human visual gamma for color stimuli: When LGN drive is equalized, red is not special

Strong gamma-band oscillations in primate early visual cortex can be induced by spatially homogeneous, high-contrast stimuli, such as color surfaces. Compared to other hues, particularly strong gamma oscillations have been reported for red stimuli. However, precortical color processing and the resultant strength of input to V1 has often not been fully controlled for. This leaves the possibility that stronger responses to some hues were due to differences in V1 input strength. We presented stimuli that had equal luminance and color contrast levels in a color coordinate system based on color responses of the lateral geniculate nucleus, the main input source for area V1. With these stimuli, we recorded magnetoencephalography in 30 human subjects. We found narrowband color-induced gamma oscillations in early visual cortex, which, contrary to previous reports, did not differ between red and green stimuli of equal L-M cone contrast. Notably, blue stimuli with contrast exclusively on the S-cone axis induced very weak gamma responses, as well as smaller event-related fields and poorer change detection performance. The strength of human color gamma responses could be well explained by the strength of thalamic input induced by each hue and does not show a clear red bias when this input strength is properly equalized.

neuroscience↗

Multi-area recordings and optogenetics in the awake, behaving marmoset

The common marmoset has emerged as a key primate model in neuroscience. Marmosets are small in size, show great potential as transgenic models and exhibit complex behaviors. These advantages place the marmoset model in the critical gap between rodents and larger primates. Thus, it is necessary to develop technology that enables monitoring and manipulation of the neural circuits underlying the behavior of the marmoset. Here, we present a novel approach to record and optogenetically manipulate neural activity in the awake, behaving marmoset. Our design utilizes a light-weight, 3D printed titanium chamber that can house several high-density silicon probes for semi-chronic recordings, while enabling simultaneous optogenetic stimulation. Surgical procedures are streamlined via custom 3D printed guides and implantation holders. We demonstrate the application of our method by recording multi- and single-unit data from areas V1 and V6 with 192 channels simultaneously, and show for the first time that optogenetic activation of excitatory neurons in area V6 can influence behavior in a detection task. Together, the work presented here will support future studies investigating the neural basis of perception and behavior in the marmoset.

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The role of anatomical connection strength for interareal communication in macaque cortex

What is the relationship between anatomical connection strength and rhythmic synchronization? Simultaneous recordings of 15 cortical areas in two macaque monkeys show that interareal networks are functionally organized in spatially distinct modules with specific synchronization frequencies, i.e. frequency-specific functional connectomes. We relate the functional interactions between 91 area pairs to their anatomical connection strength defined in a separate cohort of twenty six subjects. This reveals that anatomical connection strength predicts rhythmic synchronization and vice-versa, in a manner that is specific for frequency bands and for the feedforward versus feedback direction, even if interareal distances are taken into account. These results further our understanding of structure-function relationships in large-scale networks covering different modality-specific brain regions and provide strong constraints on mechanistic models of brain function. Because this approach can be adapted to non-invasive techniques, it promises to open new perspectives on the functional organization of the human brain.

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Cortical resonance selects coherent input

Synchronization has been implicated in neuronal communication, but causal evidence remains indirect. We used optogenetics to generate depolarizing currents in pyramidal neurons of cat visual cortex, emulating excitatory synaptic inputs under precise temporal control, while measuring spike output. Cortex transformed constant excitation into strong gamma-band synchronization, revealing the well-known cortical resonance. Increasing excitation with ramps increased the strength and frequency of synchronization. Slow, symmetric excitation profiles revealed hysteresis of power and frequency. Crucially, white-noise input sequences enabled causal analysis of network transmission, establishing that cortical resonance selectively transmits coherent input components. Models composed of recurrently coupled excitatory and inhibitory units uncovered a crucial role of feedback inhibition and suggest that hysteresis can arise through spike-frequency adaptation. The presented approach provides a powerful means to investigate the resonance properties of local circuits and probe how these properties transform input and shape transmission.

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Stimulus-specific plasticity of macaque V1 spike rates and gamma

When a visual stimulus is repeated, average neuronal responses typically decrease, yet they might maintain or even increase their impact through increased synchronization. Previous work has found that many repetitions of a grating lead to increasing gamma-band synchronization. Here we show in awake macaque area V1 that both, repetition-related reductions in firing rate and increases in gamma are specific to the repeated stimulus. These effects showed some persistence on the timescale of minutes. Further, gamma increases were specific to the presented stimulus location. Importantly, repetition effects on gamma and on firing rates generalized to natural images. These findings suggest that gamma-band synchronization subserves the adaptive processing of repeated stimulus encounters, both for generating efficient stimulus responses and possibly for memory formation.

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Stimulus-specific plasticity in human visual gamma-band activity and functional connectivity

Under natural conditions, the visual system often sees a given input repeatedly. This provides an opportunity to optimize processing of the repeated stimuli. Stimulus repetition has been shown to strongly modulate neuronal-gamma band synchronization, yet crucial questions remained open. Here we used magnetoencephalography in 30 human subjects and find that gamma decreases across ~10 repetitions and then increases across further repetitions, revealing plastic changes of the activated neuronal circuits. Crucially, changes induced by one stimulus did not affect responses to other stimuli, demonstrating stimulus specificity. Changes partially persisted when the inducing stimulus was repeated after 25 minutes of intervening stimuli. They were strongest in early visual cortex and increased interareal feedforward influences. Our results suggest that early visual cortex gamma synchronization enables adaptive neuronal processing of recurring stimuli. These and previously reported changes might be due to an interaction of oscillatory dynamics with established synaptic plasticity mechanisms.

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Head-free eye tracking, and efficient receptive field mapping in the marmoset

The marmoset has emerged as a promising primate model system, in particular for visual neuroscience. Many common experimental paradigms rely on head fixation and an extended period of eye fixation during the presentation of salient visual stimuli. Both of these behavioral requirements can be challenging for marmosets. Here, we present two methodological developments, each addressing one of these difficulties. First, we show that it is possible to use a standard eye tracking system without head fixation to assess visual behavior in the marmoset. Eye tracking quality from head-free animals is sufficient to obtain precise psychometric functions from a visual acuity task. Secondly, we introduce a novel method for efficient receptive field mapping that does not rely on moving stimuli but uses fast flashing annuli and wedges. We present data recorded during head-fixation in areas V1 and V6 and show that receptive field locations are readily obtained within a short period of recording time. Thus, the methodological advancements presented in this work will contribute to establish the marmoset as a valuable model in neuroscience.

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Predictability in natural images determines V1 firing rates and synchronization: A deep neural network approach

Predictive coding is an important candidate theory of self-supervised learning in the brain. Its central idea is that neural activity results from an integration and comparison of bottom-up inputs with contextual predictions, a process in which firing rates and synchronization may play distinct roles. Here, we quantified stimulus predictability for natural images based on self-supervised, generative neural networks. When the precise pixel structure of a stimulus falling into the V1 receptive field (RF) was predicted by the spatial context, V1 exhibited characteristic{gamma} -synchronization (30-80Hz), despite no detectable modulation of firing rates. In contrast to{gamma} , {beta}-synchronization emerged exclusively for unpredictable stimuli. Natural images with high structural predictability were characterized by high compressibility and low dimensionality. Yet, perceptual similarity was mainly determined by higher-level features of natural stimuli, not by the precise pixel structure. When higher-level features of the stimulus in the receptive field were predicted by the context, neurons showed a strong reduction in firing rates and an increase in surround suppression that was dissociated from synchronization patterns. These findings reveal distinct roles of synchronization and firing rates in the predictive coding of natural images.

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Gamma-rhythmic input causes spike output

The gamma rhythm has been implicated in neuronal communication, but causal evidence remains indirect. We measured spike output of local neuronal networks and emulated their synaptic input through optogenetics. Opsins provide currents through somato-dendritic membranes, similar to synapses, yet under experimental control with high temporal precision. We expressed Channelrhodopsin-2 in excitatory neurons of cat visual cortex and recorded neuronal responses to light with different temporal characteristics. Sine waves of different frequencies entrained neuronal responses with a reliability that peaked for input frequencies in the gamma band. Crucially, we also presented white-noise sequences, because their temporal unpredictability enables analysis of causality. Neuronal spike output was caused specifically by the inputs gamma component. This gamma-specific transfer function is likely an emergent property of in-vivo networks with feedback inhibition. The method described here could reveal the transfer function between the input to any one and the output of any other neuronal group.

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Cortical network mechanisms of response inhibition

Both the right inferior frontal gyrus (rIFG) and the pre-supplementary motor area (pre-SMA) are crucial for successful response inhibition. However, the particular functional roles of those two regions have been controversially debated for more than a decade now. It is unclear whether the rIFG directly initiates stopping or serves an attentional function, whereas the stopping is triggered by the pre-SMA. The current multimodal MEG/fMRI study sought to clarify the role and temporal activation order of both regions in response inhibition using a selective stopping task. This task dissociates inhibitory from attentional processes. Our results reliably reveal a temporal precedence of rIFG over pre-SMA. Moreover, connectivity during response inhibition is directed from rIFG to pre-SMA and predicts stopping performance. Response inhibition is implemented via beta-band oscillations. Our findings support the hypothesis that response inhibition is initiated by the rIFG as a form of attention-independent top-down control.

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Brain rhythms shift and deploy attention

One of the most central cognitive functions is attention. Its neuronal underpinnings have primarily been studied during conditions of sustained attention. Much less is known about the neuronal dynamics underlying the processes of shifting attention in space, as compared to maintaining it on one stimulus, and of deploying it to a particular stimulus. Here, we use ECoG to investigate four rhythms across large parts of the left hemisphere of two macaque monkeys during a task that allows investigation of deployment and shifting. Shifting involved a strong transient enhancement of power in a 2-7 Hz theta band in frontal, pre-motor and visual areas, and reductions of power in an 11-20 Hz beta band in a fronto-centro-parietal network and in a 29-36 Hz high-beta band in premotor cortex. Deployment of attention to the contralateral hemifield involved an enhancement of beta power in parietal areas, a concomitant reduction of high-beta power in pre-motor areas and an enhancement of power in a 60-76 Hz gamma band in extra-striate cortex. Effects due to shifting occurred earlier than effects due to deployment. These results demonstrate that the four investigated rhythms are involved in attentional allocation, with striking differences between shifting and deployment between different brain areas.\n\nSignificanceWe are often confronted by many visual stimuli, and attentional mechanisms select one stimulus for in-depth processing. This involves that attention is shifted between stimuli and deployed to one stimulus at a time. Prior studies have revealed that these processes are subserved by several brain rhythms. Therefore, we recorded brain activity in macaque monkeys with many electrodes distributed over large parts of their left hemisphere, while they performed a task that involved shifting and deploying attention. We found four dominant rhythms: theta (2-7 Hz), beta (11-20 Hz), high-beta (29-36 Hz) and gamma (60-76 Hz). Attentional shifting and deployment involved dynamic modulations in the strength of those rhythms with high specificity in space and time.

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Gamma-cycle duration predicts instantaneous amplitude, spike rate and synchrony in macaque V1.

Circuits of excitatory and inhibitory neurons can generate rhythmic activity in the gamma frequency-range (30-80Hz). Individual gamma-cycles show spontaneous variability in amplitude and duration. The mechanisms underlying this variability are not fully understood. We recorded local-field-potentials (LFPs) and spikes from awake macaque V1, and developed a noise-robust method to detect gamma-cycle amplitudes and durations. Amplitudes and durations showed a weak but positive correlation. This correlation, and the joint amplitude-duration distribution, is well reproduced by a dampened harmonic oscillator driven by stochastic noise. We show that this model accurately fits LFP power spectra and is equivalent to a linear PING (Pyramidal Interneuron Network Gamma) circuit. The model recapitulates two additional features of V1 gamma: (1) Amplitude-duration correlations decrease with oscillation strength; (2) Amplitudes and durations exhibit strong and weak autocorrelations, respectively, depending on oscillation strength. Finally, longer gamma-cycles are associated with stronger spike-synchrony, but lower spike-rates in both (putative) excitatory and inhibitory neurons. In sum, V1 gamma-dynamics are well described by the simplest possible model of gamma: A linear harmonic oscillator driven by noise.

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A distinct class of bursting neurons with strong gamma synchronization and stimulus selectivity in monkey V1

Cortical computation depends on interactions between excitatory and inhibitory neurons. The contributions of distinct neuron-types to sensory processing and network synchronization in primate visual-cortex remain largely undetermined. We show that in awake monkey V1, there exists a distinct cell-type ({approx}30% of neurons) that has narrow-waveform action-potentials, high spontaneous discharge-rates, and fires in high-frequency bursts. These neurons are more stimulus-selective and phase-locked to gamma (30-80Hz) oscillations as compared to other neuron types. Unlike the other neuron-types, their gamma phase-locking is highly predictive of their orientation tuning. We find evidence for strong rhythmic inhibition in these neurons, suggesting that they interact with interneurons to act as excitatory pacemakers for the V1 gamma rhythm. These neurons have not been observed in other primate cortical areas and we find that they are not present in rodent V1. However, they resemble the excitatory \"chattering\" neurons previously identified by intracellular recordings in cat V1. Given its properties, this neuron type should be pivotal for the encoding and transmission of V1 stimulus information.

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Hippocampal and neocortical oscillations are tuned to behavioral state in freely-behaving macaques

Wireless recordings in macaque neocortex and hippocampus showed stronger theta oscillations during early-stage sleep than during alert volitional movement including walking. In contrast, hippocampal beta and gamma oscillations were prominent during walking and other active behaviors. These relations between hippocampal rhythms and behavioral states in the primate differ markedly from those observed in rodents. Primate neocortex showed similar changes in spectral content across behavioral state as the hippocampus.

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