Neuron participation in a synchrony-encoding assembly

BACKGROUND: Synchronization of action potentials between neurons is considered to be an encoding process that allows the grouping of various and multiple features of an image leading to a coherent perception. How this coding neuronal assembly is configured is debated. We have previously shown that the magnitude of synchronization between excited neurons is stimulus-dependent. In the present investigation we compare the levels of synchronization between synchronizing individual neurons and the synchronizing pool of cells to which they belong. RESULTS: Even though neurons belonged to their respective pools, some cells synchronized for all presented stimuli while others were rather selective and only a few stimulating conditions produced a significant synchronization. In addition the experiments show that one synchronizing pair rarely replicates the level of synchrony between corresponding groups of units. But when synchronizing clusters of neurons increase in number, the correlation (measured as a coefficient of determination) between unit synchronization and the synchronization between the entire pools of cells to which individual neurons belong improves. CONCLUSION: These results prompt the hypothesis that random or spontaneous synchronization becomes progressively less important, whereas coincident spikes related to encoding properties of targets gain significance because a particular configuration of an image biases the excitatory inputs in favor of connections driven by the applied features of the stimulus

GABAergic inhibition shapes interictal dynamics in awake epileptic mice

International audienceEpilepsy is characterized by recurrent seizures and brief, synchronous bursts called interictal spikes that are present in-between seizures and observed as transient events in EEG signals. While GABAergic transmission is known to play an important role in shaping healthy brain activity, the role of inhibition in these pathological epileptic dynamics remains unclear. Examining the microcircuits that participate in interictal spikes is thus an important first step towards addressing this issue, as the function of these transient synchronizations in either promoting or prohibiting seizures is currently under debate. To identify the microcircuits recruited in spontaneous interictal spikes in the absence of any proconvulsive drug or anaesthetic agent, we combine a chronic model of epilepsy with in vivo two-photon calcium imaging and multiunit extracellular recordings to map cellular recruitment within large populations of CA1 neurons in mice free to run on a self-paced treadmill. We show that GABAergic neurons, as opposed to their glutamatergic counterparts, are preferentially recruited during spontaneous interictal activity in the CA1 region of the epileptic mouse hippocampus. Although the specific cellular dynamics of interictal spikes are found to be highly variable, they are consistently associated with the activation of GABAergic neurons, resulting in a perisomatic inhibitory restraint that reduces neuronal spiking in the principal cell layer. Given the role of GABAergic neurons in shaping brain activity during normal cognitive function, their aberrant unbalanced recruitment during these transient events could have important downstream effects with clinical implications

Transformation of perception from sensory to motor cortex

To better understand how a stream of sensory data is transformed into a percept, we examined neuronal activity in vibrissal sensory cortex, vS1, together with vibrissal motor cortex, vM1 (a frontal cortex target of vS1), while rats compared the intensity of two vibrations separated by an interstimulus delay. Vibrations were ‘‘noisy,’’ constructed by stringing together over time a sequence of velocity values sampled from a normal distribution; each vibration’s mean speed was proportional to the width of the normal distribution. Durations of both stimulus 1 and stimulus 2 could vary from 100 to 600 ms. Psychometric curves reveal that rats overestimated the longer-duration stimulus—thus, perceived intensity of a vibration grew over the course of hundreds of milliseconds even while the sensory input remained, on average, stationary. Human subjects demonstrated the identical perceptual phenomenon, indicating that the underlying mechanisms of temporal integration generalize across species. The time dependence of the percept allowed us to ask to what extent neurons encoded the ongoing stimulus stream versus the animal’s percept.We demonstrate that vS1 firing correlated with the local features of the vibration, whereas vM1 firing correlated with the percept: the final vM1 population state varied, as did the rat’s behavior, according to both stimulus speed and stimulus duration. Moreover, vM1 populations appeared to participate in the trace of the percept of stimulus 1 as the rat awaited stimulus 2. In conclusion, the transformation of sensory data into the percept appears to involve the integration and storage of vS1 signals by vM1

Unveiling fast field oscillations through comodulation

Phase-amplitude coupling analysis shows that theta phase modulates oscillatory activity not only within the traditional gamma band (30–100 Hz) but also at faster frequencies, called high-frequency oscillations (HFOs; 120–160 Hz). To date, however, theta-associated HFOs have been reported by only a small number of laboratories. Here we characterized coupling patterns during active waking (aWk) and rapid eye movement (REM) sleep in local field potentials (LFPs) from the parietal cortex and hippocampus of rats, focusing on how theta-associated HFOs can be detected. We found that electrode geometry and impedance only mildly influence HFO detection, whereas recording location and behavioral state are main factors. HFOs were most prominent in parietal cortex and during REM sleep, although they could also be detected in stratum oriens-alveus and during aWK. The underreporting of HFOs may thus be a result of higher prevalence of recordings from the pyramidal cell layer. However, at this layer, spike-leaked HFOs (SLHFOs) dominate, which represent spike contamination of the LFP and not genuine oscillations. In contrast to HFOs, high-gamma (HG; 60–100 Hz) coupled to theta below the pyramidal cell layer; theta–HG coupling increased during REM sleep. Theta also weakly modulated low-gamma (LG; 30–60 Hz) amplitude, mainly in the parietal cortex; theta–LG coupling did not vary between aWK and REM sleep. HG and HFOs were maximal near the theta peak, parietal LG at the ascending phase, hippocampal LG at the descending phase, and SLHFOs at the trough. Our results unveil four types of fast LFP activity coupled to theta and outline how to detect theta-associated HFOs

Mechanisms of Feedback in the Visual System

Feedback is an ubiquitous feature of neural systems though there is little consensus on the roles of mechanisms involved with feedback. We set up an in vivo preparation to study and characterize an accessible and isolated feedback loop within the visual system of the leopard frog, Rana pipiens. We recorded extracellularly within the nucleus isthmi, a nucleus providing direct topographic feedback to the optic tectum, a nucleus that receives the vast majority of retinal output. The optic tectum and nucleus isthmi of the amphibian are homologous structures to the superior colliculus and parabigeminal nucleus in mammals, respectively. We formulated a novel threshold for detecting neuronal spikes within a low signal-to-noise environment, as exists in the nucleus isthmi due to its high density of small neuronal cell bodies. Combining this threshold with a recently developed spike sorting procedure enabled us to extract simultaneous recordings from up to 7 neurons at a time from a single extracellular electrode. We then stimulated the frog using computer driven dynamic spatiotemporal visual stimuli to characterize the responses of the nucleus isthmi neurons. We found that the responses display surprisingly long time courses to simple visual stimuli. Furthermore, we found that when stimulated with complex contextual stimuli the response of the nucleus isthmi is quite counter-intuitive. When a stimulus is presented outside of the classical receptive field along with a stimulus within the receptive field, the response is actually higher than the response to just a stimulus within the classical receptive field. Finally, we compared the responses of all of the simultaneously recorded neurons and, together with data from in vitro experiments within the nucleus isthmi, conclude that the nucleus isthmi of the frog is composed of just one electrophysiological population of cells

The functional organization of area V2, I: Specialization across stripes and layers

We used qualitative tests to assess the sensitivity of 1043 V2 neurons (predominantly multiunits) in anesthetised macaque monkeys to direction, length. orientation. and color of moving bar stimuli. Spectral sensitivity was additionally tested by noting ON or OFF responses to flashed stimuli of varied size and color. The location of 649 units was identified with respect to cycles of cytochrome oxidase stripes (thick-inter-thin-inter) and cortical layer. We used an initial 8-way stripe classification (4 stripes. and 4 "marginal" zones at interstripes boundaries), and a 9-way layer classification (5 standard layers (2-6), and 4 "marginal" Strata at layer boundaries). These classes were collapsed differently for particular analyses of functional distribution:. the main stripe-by-layer analysis was performed on 18 compartments (3 stripes X 6 layers), We found direction sensitivity only within thick stripes, orientation sensitivity mainly in thick stripes and interstripes. and spectral sensitivity mainly in thin stripes. Positive length summation was relatively more frequent in thick stripes and interstripes. and negative length/size summation in thin stripes. All these "majority" characteristics of stripes were most prominent in layers 3A and 3B. By contrast, "minority" characteristics (e.g. spectral sensitivity in thick stripes positive size summation in thin stripes) tended to be most frequent in the outer layers, that is, layers 2 and 6. In consequence, going by the four functions tested, the distinctions between stripes were maximal in layer 3, moderate in layer 2, and minimal in layer 6. Pooling all layers, there was some indication of asymmetry in the stripe cycle, in that thin stripe characteristics (spectral sensitivity, orientation insensitivity, and negative size summation) were also evident in the marginal zone and interstripe immediately lateral to a thin stripe, but less so medially. Within thin stripes, spectral and orientation selectivities were negatively correlated this was still more accentuated amongst the minority spectrally tuned cells of thick stripes. but absent from interstripes, where these two properties were randomly assorted. Directional and spectral sensitivities were each coupled to negative size summation. but not to each other. We conclude that these functional characteristics of stripes are consistent with segregated. specialized pathways ascending through their middle layers, whilst the outer layers. 1, 2, and 6, utilize feedback from higher areas to adopt a more integrative role

J Neural Eng

ObjectiveBrain-machine interfaces (BMIs) seek to enable people with movement disabilities to directly control prosthetic systems with their neural activity. Current high performance BMIs are driven by action potentials (spikes), but access to this signal often diminishes as sensors degrade over time. Decoding local field potentials (LFPs) as an alternative or complementary BMI control signal may improve performance when there is a paucity of spike signals. To date only a small handful of LFP decoding methods have been tested online; there remains a need to test different LFP decoding approaches and improve LFP-driven performance. There has also not been a reported demonstration of a hybrid BMI that decodes kinematics from both LFP and spikes. Here we first evaluate a BMI driven by the local motor potential (LMP), a low-pass filtered time-domain LFP amplitude feature. We then combine decoding of both LMP and spikes to implement a hybrid BMI.ApproachSpikes and LFP were recorded from two macaques implanted with multielectrode arrays in primary and premotor cortex while they performed a reaching task. We then evaluated closed-loop BMI control using biomimetic decoders driven by LMP, spikes, or both signals together.Main ResultsLMP decoding enabled quick and accurate cursor control which surpassed previously reported LFP BMI performance. Hybrid decoding of both spikes and LMP improved performance when spikes signal quality was mediocre to poor.SignificanceThese findings show that LMP is an effective BMI control signal which requires minimal power to extract and can substitute for or augment impoverished spikes signals. Use of this signal may lengthen the useful lifespan of BMIs and is therefore an important step towards clinically viable BMIs.8DP1HD075623/DP/NCCDPHP CDC HHS/United StatesDP1 HD075623/HD/NICHD NIH HHS/United StatesR01 NS076460/NS/NINDS NIH HHS/United StatesR01 NS076460/NS/NINDS NIH HHS/United StatesT32 MH020016/MH/NIMH NIH HHS/United States2016-06-01T00:00:00Z25946198PMC445745

Neurons in Cat Primary Visual Cortex cluster by degree of tuning but not by absolute spatial phase or temporal response phase

Neighboring neurons in cat primary visual cortex (V1) have similar preferred orientation, direction, and spatial frequency. How diverse is their degree of tuning for these properties? Are they also clustered in their tuning for the spatial phase of a flashed grating ("absolute spatial phase") or the temporal phase of a drifting grating ("temporal response phase")? To address these questions, we used tetrode recordings to simultaneously isolate multiple cells at single recording sites and record their responses to flashed and drifting gratings of multiple orientations, spatial frequencies, and spatial/temporal phases. We recorded the responses of 761 cells presented with drifting gratings and 409 cells presented with flashed gratings. We found that orientation tuning width, spatial frequency tuning width and direction selectivity index all showed significant clustering. Absolute spatial phase and temporal response phase, however, showed no clustering. We also present an algorithm that improves the performance of spike-sorting algorithms, for use in analyzing cells recorded using tetrodes. A cluster of spikes corresponding to a putative cell obtained through automatic or manual spike sorting algorithms may contain spikes from other cells with similarly-shaped waveforms. Our algorithm preferentially removes contaminating spikes from other cells, thereby decreasing the level of contamination of each unit. We call this procedure "pruning", as it entails removing portions of the cluster that are determined to be more likely to contain contaminating spikes than the cluster as a whole. Testing of the algorithm on data in which "ground truth" is known shows excellent performance, for example on average giving a percentage reduction in false positive spikes 8.2 times the percentage reduction in true positive spikes, and reducing the degree of contamination by an average of about 13%