882 research outputs found
Q&A Nikos K. Logothetis
No full textIn a candid interview with Neuron, Nikos K. Logothetis shares memories about his rich scientific past and argues about the importance of animal research and the role of science in society. He also talks about his new job and future plans as co-director of the International Center for Primate Brain Research in Shanghai
Optimal Band Separation of Extracellular Field Potentials
No full textLocal Field Potentials (LFPs) exhibit a broadband spectral structure that is traditionally partitioned into distinct frequency bands which are thought to originate from different types of neural events triggered by different processing pathways. However, the exact frequency boundaries of these processes are not known and, as a result, the frequency bands are often selected based on intuition, previous literature or visual inspection of the data. Here, we address these problems by developing a rigorous method for defining LFP frequency bands and their boundaries. The criterion introduced for determining the boundaries delimiting the bands is to maximize the information about an external correlate carried jointly by all bands in the partition. The method first partitions the LFP frequency range into two bands and then successively increases the number of bands in the partition. We applied the partitioning method to LFPs recorded from primary visual cortex of anaesthetized macaques, and we determined the optimal band partitioning that describes the encoding of naturalistic visual stimuli. The first optimal boundary partitioned the LFP response at 60 Hz into low and high frequencies, which had been previously found to convey independent information about the natural movie correlate. The second optimal boundary divided the high-frequency range at approximately 100 Hz into gamma and high-gamma frequencies, consistent with recent reports that these two bands reflect partly distinct neural processes. A third important boundary was at 25 Hz and it split the LFP range below 50 Hz into a stimulus-informative and a stimulus-independent band
Encoding of naturalistic stimuli by local field potential spectra in networks of excitatory and inhibitory neurons.
No full textRecordings of local field potentials (LFPs) reveal that the sensory cortex displays rhythmic activity and fluctuations over a wide range of frequencies and amplitudes. Yet, the role of this kind of activity in encoding sensory information remains largely unknown. To understand the rules of translation between the structure of sensory stimuli and the fluctuations of cortical responses, we simulated a sparsely connected network of excitatory and inhibitory neurons modeling a local cortical population, and we determined how the LFPs generated by the network encode information about input stimuli. We first considered simple static and periodic stimuli and then naturalistic input stimuli based on electrophysiological recordings from the thalamus of anesthetized monkeys watching natural movie scenes. We found that the simulated network produced stimulus-related LFP changes that were in striking agreement with the LFPs obtained from the primary visual cortex. Moreover, our results demonstrate that the network encoded static input spike rates into gamma-range oscillations generated by inhibitory-excitatory neural interactions and encoded slow dynamic features of the input into slow LFP fluctuations mediated by stimulus-neural interactions. The model cortical network processed dynamic stimuli with naturalistic temporal structure by using low and high response frequencies as independent communication channels, again in agreement with recent reports from visual cortex responses to naturalistic movies. One potential function of this frequency decomposition into independent information channels operated by the cortical network may be that of enhancing the capacity of the cortical column to encode our complex sensory environment
Cortical dynamics during naturalistic sensory stimulations: Experiments and models
No full textWe report the results of our experimental and theoretical investigations of the neural response dynamics in primary visual cortex (V1) during naturalistic visual stimulation. We recorded Local Field Potentials (LFPs) and spiking activity from V1 of anaesthetized macaques during binocular presentation of Hollywood color movies. We analyzed these recordings with information theoretic methods, and found that visual information was encoded mainly by two bands of LFP responses: the network fluctuations measured by the phase and power of low-frequency (less than 12 Hz) LFPs; and fast gamma-range (50–100 Hz) oscillations. Both the power and phase of low frequency LFPs carried information largely complementary to that carried by spikes, whereas gamma range oscillations carried information largely redundant to that of spikes. To interpret these results within a quantitative theoretical framework, we then simulated a sparsely connected recurrent network of excitatory and inhibitory neurons receiving slowly varying naturalistic inputs, and we determined how the LFPs generated by the network encoded information about the inputs. We found that this simulated recurrent network reproduced well the experimentally observed dependency of LFP information upon frequency. This network encoded the overall strength of the input into the power of gamma-range oscillations generated by inhibitory–excitatory neural interactions, and encoded slow variations in the input by entraining the network LFP at the corresponding frequency. This dynamical behavior accounted quantitatively for the independent information carried by high and low frequency LFPs, and for the experimentally observed cross-frequency coupling between phase of slow LFPs and the power of gamma LFPs. We also present new results showing that the model’s dynamics also accounted for the extra visual information that the low-frequency LFP phase of spike firing carries beyond that carried by spike rates. Overall, our results suggest biological mechanisms by which cortex can multiplex information about naturalistic sensory environments
Perception of Temporally Interleaved Ambiguous Patterns
No full textAbstractBackground: Continuous viewing of ambiguous patterns is characterized by wavering perception that alternates between two or more equally valid visual solutions. However, when such patterns are viewed intermittently, either by repetitive presentation or by periodic closing of the eyes, perception can become locked or “frozen” in one configuration for several minutes at a time. One aspect of this stabilization is the possible existence of a perceptual memory that persists during periods in which the ambiguous stimulus is absent. Here, we use a novel paradigm of temporally interleaved ambiguous stimuli to explore the nature of this memory, with particular regard to its potential impact on perceptual organization.Results: We found that the persistence of a perceptual configuration was robust to interposed visual patterns, and, further, that at least three ambiguous patterns, when interleaved in time, could undergo parallel, stable time courses. Then, using an interleaved presentation paradigm, we established that the occasional reversal in one pattern could be coupled with that of its interleaved counterpart, and that this coupling was a function of the structural similarity between the patterns.Conclusions: We postulate that the stabilization observed with repetitive presentation of ambiguous patterns can be at least partially accounted for by processes that retain a recent perceptual interpretation, and we speculate that such memory may be important in natural vision. We further propose that the interleaved paradigm introduced here may be of great value to gauge aspects of stimulus similarity that appeal to particular mechanisms of perceptual organization
Local field potential reflects perceptual suppression in monkey visual cortex
No full textNeurophysiological and functional imaging experiments remain in apparent disagreement on the role played by the earliest stages of the visual cortex in supporting a visual percept. Here, we report electrophysiological findings that shed light on this issue. We monitored neural activity in the visual cortex of monkeys as they reported their perception of a high-contrast visual stimulus that was induced to vanish completely from perception on a subset of trials. We found that the spiking of neurons in cortical areas V1 and V2 was uncorrelated with the perceptual visibility of the target, whereas that in area V4 showed significant perception-related changes. In contrast, power changes in the lower frequency bands (particularly 930 Hz) of the local field potential (LFP), collected on the same trials, showed consistent and sustained perceptual modulation in all three areas. In addition, for the gamma frequency range (3050 Hz), the responses during perceptual suppression of the target were correlated significan
tly with the responses to its physical removal in all areas, although the modulation magnitude was considerably higher in area V4 than in V1 and V2. These results, taken together, suggest that low-frequency LFP power in early cortical processing is more closely related to the representation of stimulus visibility than is spiking or higher frequency LFP activity
Generalized Flash Suppression of Salient Visual Targets
No full textAbstractA pattern of light striking the retina of an alert observer is normally readily perceived. While a handful of conditions exist in which even salient visual stimuli can be rendered invisible, the mechanisms underlying such suppression remain poorly understood. Here, we describe experiments using a novel stimulation sequence that gives rise to the sudden and reliable subjective disappearance of a wide range of visual patterns. We found that a parafoveal target immediately vanished from perception following the abrupt onset of a surrounding texture. The probability of disappearance was influenced by the ocular configuration of the target and surround, as well as their spatial separation. In addition, suppression was critically dependent upon several hundred milliseconds of stimulus-specific adaptation. These findings demonstrate that the all-or-none disappearance of a salient visual target, which is reminiscent of a high-level selection process, is inextricably linked to topographic stimulus representations, presumably in the early visual cortex
Stable perception of visually ambiguous patterns
No full textDuring the viewing of certain patterns, widely known as ambiguous or puzzle figures, perception lapses into a sequence of spontaneous alternations, switching every few seconds between two or more visual interpretations of the stimulus. Although their nature and origin remain topics of debate, these stochastic switches are generally thought to be the automatic and inevitable consequence of viewing a pattern without a unique solution. We report here that in humans such perceptual alternations can be slowed, and even brought to a standstill, if the visual stimulus is periodically removed from view. We also show, with a visual illusion, that this stabilizing effect hinges on perceptual disappearance rather than on actual removal of the stimulus. These findings indicate that uninterrupted subjective perception of an ambiguous pattern is required for the initiation of the brain-state changes underlying multistable vision
Sensory neural codes using multiplexed temporal scales
No full textDetermining how neuronal activity represents sensory information is central for understanding perception. Recent work shows that neural responses at different timescales can encode different stimulus attributes, resulting in a temporal multiplexing of sensory information. Multiplexing increases the encoding capacity of neural responses, enables disambiguation of stimuli that cannot be discriminated at a single response timescale, and makes sensory representations stable to the presence of variability in the sensory world. Thus, as we discuss here, temporal multiplexing could be a key strategy used by the brain to form an information-rich and stable representation of the environment
Understanding the relationships between spike rate and delta/gamma frequency bands of LFPs and EEGs using a local cortical network model
No full textDespite the widespread use of EEGs to measure the large-scale dynamics of the human brain, little is known on how the dynamics of EEGs relates to that of the underlying spike rates of cortical neurons. However, progress was made by recent neurophysiological experiments reporting that EEG delta-band phase and gamma-band amplitude reliably predict some complementary aspects of the time course of spikes of visual cortical neurons. To elucidate the mechanisms behind these findings, here we hypothesize that the EEG delta phase reflects shifts of local cortical excitability arising from slow fluctuations in the network input due to entrainment to sensory stimuli or to fluctuations in ongoing activity, and that the resulting local excitability fluctuations modulate both the spike rate and the engagement of excitatoryinhibitory loops producing gamma-band oscillations. We quantitatively tested these hypotheses by simulating a recurrent network of excitatory and inhibitory neurons stimulated with dynamic inputs presenting temporal regularities similar to that of thalamic responses during naturalistic visual stimulation and during spontaneous activity. The network model reproduced in detail the experimental relationships between spike rate and EEGs, and suggested that the complementariness of the prediction of spike rates obtained from EEG delta phase or gamma amplitude arises from nonlinearities in the engagement of excitatoryinhibitory loops and from temporal modulations in the amplitude of the network input, which respectively limit the predictability of spike rates from gamma amplitude or delta phase alone. The model suggested also ways to improve and extend current algorithms for online prediction of spike rates from EEGs
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