Spiking Activity Of Single Neurons Research Articles

Single-neuron mechanisms of neural adaptation in the human temporal lobe

A central function of the human brain is to adapt to new situations based on past experience. Adaptation is reflected behaviorally by shorter reaction times to repeating or similar stimuli, and neurophysiologically by reduced neural activity in bulk-tissue measurements with fMRI or EEG. Several potential single-neuron mechanisms have been hypothesized to cause this reduction of activity at the macroscopic level. We here explore these mechanisms using an adaptation paradigm with visual stimuli bearing abstract semantic similarity. We recorded intracranial EEG (iEEG) simultaneously with spiking activity of single neurons in the medial temporal lobes of 25 neurosurgical patients. Recording from 4917 single neurons, we demonstrate that reduced event-related potentials in the macroscopic iEEG signal are associated with a sharpening of single-neuron tuning curves in the amygdala, but with an overall reduction of single-neuron activity in the hippocampus, entorhinal cortex, and parahippocampal cortex, consistent with fatiguing in these areas.

Recording local field potential and neuronal activity with tetrodes in epileptic patients

BackgroundRecordings with tetrodes have proven to be more effective in isolating single neuron spiking activity than with single microwires. However, tetrodes have never been used in humans. We report on the characteristics, safety, compatibility with clinical intracranial recordings in epileptic patients, and performance, of a new type of hybrid electrode equipped with tetrodes. New method240 standard clinical macroelectrodes and 102 hybrid electrodes were implanted in 28 patients. Hybrids (diameter 800 μm) are made of 6 or 9 macro-contacts and 2 or 3 tetrodes (diameter 70−80 μm). ResultsNo clinical complication or adverse event was associated with the hybrids. Impedance and noise of recordings were stable over time. The design enabled multiscale spatial analyses that revealed physiopathological events which were sometimes specific to one tetrode, but could not be recorded on the macro-contacts. After spike sorting, the single-unit yield was similar to other hybrid electrodes and was sometimes as high as >10 neurons per tetrode. Comparison with existing method(s)This new hybrid electrode has a smaller diameter than other available hybrid electrodes. It provides novel spatial information due to the configuration of the tetrodes. The single-unit yield appears promising. ConclusionsThis new hybrid electrode is safe, easy to use, and works satisfactorily for conducting multi-scale seizure and physiological analyses.

Neural effects of transcranial magnetic stimulation at the single-cell level

Transcranial magnetic stimulation (TMS) can non-invasively modulate neural activity in humans. Despite three decades of research, the spatial extent of the cortical area activated by TMS is still controversial. Moreover, how TMS interacts with task-related activity during motor behavior is unknown. Here, we applied single-pulse TMS over macaque parietal cortex while recording single-unit activity at various distances from the center of stimulation during grasping. The spatial extent of TMS-induced activation is remarkably restricted, affecting the spiking activity of single neurons in an area of cortex measuring less than 2 mm in diameter. In task-related neurons, TMS evokes a transient excitation followed by reduced activity, paralleled by a significantly longer grasping time. Furthermore, TMS-induced activity and task-related activity do not summate in single neurons. These results furnish crucial experimental evidence for the neural effects of TMS at the single-cell level and uncover the neural underpinnings of behavioral effects of TMS.

Place cell assemblies remain intact, despite reduced phase precession, after cholinergic disruption.

The hippocampal theta rhythm is frequently viewed as a clocking mechanism that coordinates the spiking activity of neurons across the hippocampus to form coherent neural assemblies. Phase precession is a form of temporal coding evidencing this mechanism and is degraded following systemic pharmacological disruption of cholinergic signaling. However, whether neural assemblies are commensurately degraded, as would be predicted from a clocking mechanism hypothesis, remains unknown. To address this, we recorded the spiking activity of hippocampal place cells as rats completed laps on a circle track for chocolate drink before versus during the influence of a systemic muscarinic acetylcholine receptor antagonist. We compared the integrity of hippocampal ensembles using three approaches. The first approach used cross-correlogram (CCG) analyses to ask if the relative spike-timing between pairs of cells became less reliable. The second used a general linear model based analysis to ask whether the activity of simultaneously recorded neurons became any less predictive of the spiking activity of single neurons. Finally, the third approach used a reconstruction analysis to ask if the population activity was any less informative regarding the environmental position of the animal and whether theta sequences were impaired. The results of all three analyses paint a consistent picture: systemic cholinergic disruption did not degrade assembly integrity. These data demonstrate that place cell assemblies do not depend upon high quality phase precession.

Estimating Multiscale Direct Causality Graphs in Neural Spike-Field Networks

Neural representations span various spatiotemporal scales of brain activity, from the spiking activity of single neurons to field activity measuring large-scale networks. The simultaneous analyses of spikes and fields to uncover causal interactions in multiscale networks could help understand neural mechanisms. However, assessing causality within spike-field networks is challenging as spikes are binary-valued with a fast time-scale while fields are continuous-valued with slower time-scales. Current causality measures are largely not applicable to mixed discrete-continuous network activity. Here, in this paper, we develop a novel multiscale causality estimation algorithm for spike-field networks. We construct a likelihood function comprised of point process models for spikes and linear Gaussian models for fields. For spikes, firing rates are modeled as a function of the history of both field signals and binary spike events within the network. For fields, to make their linear models consistent with biophysical findings, we use the history of field signals and the history of the latent log-firing rates of neurons as predictors. To resolve the challenge of estimating the network model parameters in the presence of latent firing rates, we develop a sequential maximum-likelihood parameter estimation procedure that extends to large networks. Once models are estimated, we compute directed information as our measure of multiscale causality and devise two statistical tests to assess its significance. Using extensive simulations, we show that the algorithm can accurately reconstruct the true causality graphs of random spike-field networks. Moreover, the algorithm is robust to the number of connections, connection strengths, or exact topology of the network. This multiscale causality estimation algorithm has important implications for studying neural mechanisms and for future neurotechnology design.

Statistical Characteristics of the Spike Activity of Neurons in the Midbrain Auditory Center in Frogs on Exposure to Tones Modulated by Low-Frequency Noise

The time parameters of the spike activity of single neurons in the brainstem part of the auditory system carry basic information on the properties of perceived signals. To characterize these parameters, the activity of single neurons in the midbrain center (semicircular torus) of the common frog (Rana temporaria) was studied on exposure to prolonged tones amplitude-modulated with repeating bursts of low-frequency noise. Time-shuffled autocorrelation functions were calculated, these corresponding to the sum of the correlation functions between responses to all bursts presented with the exception of responses evoked by one of the bursts. This approach excludes the effects of the refractory properties of the neuron being studied, allowing the responses of a single neuron to be used to evaluate the nature of the spike activity in the local population of cells with presumptively identical properties but which are statistically independent of each other. Significant variation in the statistical characteristics of output spike activity in different cells in the semicircular toroid was found, such that signals could be characterized in terms of different time properties. Neurons with highly specific reactions to the time characteristics of the envelope were observed.

Low-dimensional spike rate models derived from networks of adaptive integrate-and-fire neurons: Comparison and implementation

The spiking activity of single neurons can be well described by a nonlinear integrate-and-fire model that includes somatic adaptation. When exposed to fluctuating inputs sparsely coupled populations of these model neurons exhibit stochastic collective dynamics that can be effectively characterized using the Fokker-Planck equation. This approach, however, leads to a model with an infinite-dimensional state space and non-standard boundary conditions. Here we derive from that description four simple models for the spike rate dynamics in terms of low-dimensional ordinary differential equations using two different reduction techniques: one uses the spectral decomposition of the Fokker-Planck operator, the other is based on a cascade of two linear filters and a nonlinearity, which are determined from the Fokker-Planck equation and semi-analytically approximated. We evaluate the reduced models for a wide range of biologically plausible input statistics and find that both approximation approaches lead to spike rate models that accurately reproduce the spiking behavior of the underlying adaptive integrate-and-fire population. Particularly the cascade-based models are overall most accurate and robust, especially in the sensitive region of rapidly changing input. For the mean-driven regime, when input fluctuations are not too strong and fast, however, the best performing model is based on the spectral decomposition. The low-dimensional models also well reproduce stable oscillatory spike rate dynamics that are generated either by recurrent synaptic excitation and neuronal adaptation or through delayed inhibitory synaptic feedback. The computational demands of the reduced models are very low but the implementation complexity differs between the different model variants. Therefore we have made available implementations that allow to numerically integrate the low-dimensional spike rate models as well as the Fokker-Planck partial differential equation in efficient ways for arbitrary model parametrizations as open source software. The derived spike rate descriptions retain a direct link to the properties of single neurons, allow for convenient mathematical analyses of network states, and are well suited for application in neural mass/mean-field based brain network models.

Low-dimensional spike rate dynamics of coupled adaptive model neurons

The spiking activity of single neurons can be well described by a two-dimensional integrate-and-fire model that includes neuronal adaptation [1] caused by slowly decaying potassium currents [2]. For fluctuating inputs sparsely coupled spiking model neurons exhibit stochastic population dynamics which can be effectively characterized using the Fokker-Planck equation (see, e.g., [3-5]). This approach leads to a model with an infinite-dimensional state space and non-standard boundary conditions. However, the spike rate dynamics can be approximated by a low-dimensional ordinary differential equation in different ways [4,6,7]. Although these approximation techniques are interrelated it is not clear which reduced model best reproduces the spike rate of the original spiking network, depending on the statistics of the input. Here we first extend each of these reduction methods to account for neuronal adaptation and then evaluate the reduced models in terms of spike rate reproduction accuracy for a range of biologically plausible input statistics, computational demand and implementation complexity (see, e.g., Figure ​Figure1).1). These reduced descriptions are well suited for (i) application in neural mass/mean-field based brain network models, having a link to single neuron properties retained and being computationally efficient, and (ii) mathematical analyses of, e.g., asynchronous and rhythmic network states. Figure 1 Simulation of a large population of adaptive exponential integrate-and-fire (aEIF) neurons driven by a stochastic current with time-varying moments. Instantaneous spike rate and adaptation current averaged over 200,000 neurons are shown in gray. Overlaid ...

Combined Single Neuron Unit Activity and Local Field Potential Oscillations in a Human Visual Recognition Memory Task.

Activities of neuronal networks range from action potential firing of individual neurons, coordinated oscillations of local neuronal assemblies, and distributed neural populations. Here, we describe recordings using hybrid electrodes, containing both micro- and clinical macroelectrodes, to simultaneously sample both large-scale network oscillations and single neuron spiking activity in the medial temporal lobe structures of human subjects during a visual recognition memory task. We quantify and compare single neuron unit activity (SUA) with high-frequency macrofield oscillations (HFOs) for decoding visual images. SUA and HFOs were recorded using hybrid electrodes containing both micro and macroelectrode contacts, implanted in patients with focal epilepsy. Decoding of image properties in different task trials was performed, analyzing SUA and HFO as point processes to capture the dynamics of neurons and their assemblies at different spatiotemporal scales, ranging from submillisecond discharges of single units to fast oscillations across large neuronal populations. Results highlight the limitations and potential complementary use of SUA and HFOs for decoding of general image properties. The dynamics of SUA and HFOs can be used to explore a wide range of neuronal assembly activities engaged in human memory processing. Hybrid electrodes provide a technological bridge for exploring multiscale activity, spanning individual neurons, their assemblies, and large-scale population activity reflected in local field potentials. Analysis of SUA and HFO dynamics as point processes provides a potentially useful signal processing method for exploring the neuronal correlates operating at different spatial scales.

Single-Trial Decoding of Visual Attention from Local Field Potentials in the Primate Lateral Prefrontal Cortex Is Frequency-Dependent.

Local field potentials (LFPs) are fluctuations of extracellular voltage that may reflect the physiological phenomena occurring within a volume of neural tissue. It is known that the allocation of spatial attention modulates the amplitude of LFPs in visual areas of primates. An issue that remains poorly investigated is whether and how attention modulates LFPs in executive brain areas, such as the lateral prefrontal cortex (LPFC), thought to be involved in the origins of attention. We addressed this issue by recording LFPs from multielectrode arrays implanted in the LPFC of two macaques. We found that the allocation of attention can be reliably decoded on a single-trial basis from ensembles of LFPs with frequencies >60 Hz. Using LFP frequencies <60 Hz, we could not decode the allocation of attention, but we could decode the location of a visual stimulus as well as the endpoint of saccades toward that stimulus. The information contained in the high-frequency LFPs was fully redundant with the information contained in the spiking activity of single neurons recorded from the same electrodes. Moreover, the decoding of attention using γ frequency LFPs was less accurate than using spikes, but it was twice more stable across time. Finally, decorrelating the LFP signals from the different electrodes increased decoding performance in the high frequencies by up to ∼14%. Our findings suggest that LFPs recorded from chronically implanted multielectrode arrays in the LPFC contain information about sensory, cognitive, and motor components of a task in a frequency-dependent manner.

Juxtacellular Monitoring and Localization of Single Neurons within Sub-cortical Brain Structures of Alert, Head-restrained Rats.

There are a variety of techniques to monitor extracellular activity of single neuronal units. However, monitoring this activity from deep brain structures in behaving animals remains a technical challenge, especially if the structures must be targeted stereotaxically. This protocol describes convenient surgical and electrophysiological techniques that maintain the animal's head in the stereotaxic plane and unambiguously isolate the spiking activity of single neurons. The protocol combines head restraint of alert rodents, juxtacellular monitoring with micropipette electrodes, and iontophoretic dye injection to identify the neuron location in post-hoc histology. While each of these techniques is in itself well-established, the protocol focuses on the specifics of their combined use in a single experiment. These neurophysiological and neuroanatomical techniques are combined with behavioral monitoring. In the present example, the combined techniques are used to determine how self-generated vibrissa movements are encoded in the activity of neurons within the somatosensory thalamus. More generally, it is straightforward to adapt this protocol to monitor neuronal activity in conjunction with a variety of behavioral tasks in rats, mice, and other animals. Critically, the combination of these methods allows the experimenter to directly relate anatomically-identified neurophysiological signals to behavior.

[Development of synaptic onset latency and threshold in auditory cortex in rats].

To study the change of synaptic onset latency and threshold in primary auditory cortex (A1) during the development of SD rat. Extracellular recording was used to locate A1, followed by transferred to loose-patch and whole-cell patch in vivo to record the spike activity, synaptic onset latency and threshold responses respectively. Rats were divided into 4 groups according to ages, postnatal 12-15 days, 16-18 days, 19-24 days and adult (> 3 months). 1. The onset latency of local field potential in A1 of adult rats[(10-20)ms] was shorter than young rats[(20-30)ms]. 2. During development, the onset latency of spikes of a single neuron in response to white noise pulses decreased. And the latency in young rats P12-15 [(40.15 ± 2.67) ms] and P16-18 [(33.86 ± 4.61) ms] were longer than in adults [(22.93 ± 2.94) ms] (ANOVA-test, t = 4.330 and 1.995, P = 0.00 and 0.04) . However, the onset latencies of P19-24 [(24.80 ± 3.63) ms] and adult had no significant difference (P > 0.05). 3.Synaptic onset latencies of both excitation and inhibition were significantly longer in P12-15[ (38.94 ± 1.90) ms, (35.26 ± 2.40) ms] and P16-18[ (32.68 ± 2.52) ms, (30.24 ± 2.18) ms] than in adults [(19.4 ± 1.06) ms, (18.91 ± 0.77) ms] excitation (t = 6.255 and 4.662, P < 0.01) inhibition (t = 8.918 and 4.820, P < 0.01) showed significant difference. Whereas the onset latencies of P19-24[ (23.67 ± 2.46) ms, (21.43 ± 1.80) ms] and adults displayed no prominent difference(P > 0.01). Meanwhile, the difference between the onset latencies of excitation and inhibition became narrower during development[ (3.15 ± 1.02) ms, (2.01 ± 0.73) ms, (1.79 ± 0.85) ms, (0.39 ± 0.48) ms]. P12-15 had notably difference in comparison to adults (t = 1.739, P < 0.01). 4. The thresholds of synaptic response were notably higher in P12-15 (40.0 ± 1.6) dB and P16-18 (41.3 ± 11.6) dB when compared with adults (30.9 ± 0.6) dB (t = 5.284 and 5.867, P < 0.01) . While that of P19-24 (35.0 ± 32.7) dB showed no distinct difference (P > 0.01). Single neuron spiking activity, synaptic onset latency and threshold evoked by sound stimulus gradually mature during the development in rat A1.

Tolerance of macaque middle superior temporal sulcus body patch neurons to shape-preserving stimulus transformations.

Event Abstract Back to Event Tolerance of macaque middle superior temporal sulcus body patch neurons to shape-preserving stimulus transformations. Ivo D. Popivanov1, Jan Jastorff1, 2, Wim Vanduffel1, 3, 4, Philippe G. Schyns5 and Rufin Vogels1* 1 Katolieke Universiteit Leuven, Biomedische Wetenschapen, Belgium 2 KU Leuven, Res. Group Psychiatry, Belgium 3 MGH Martinos Ctr., United States 4 Harvard Med. Sch., United States 5 Univ. of Glasgow, Inst. of Neurosci. and Psychology, United Kingdom Previously we demonstrated that although neurons in the middle Superior Temporal Sulcus (midSTS) body patch responded greater to images of bodies than to faces and objects, the body patch neurons show profound within-class stimulus selectivity (Popivanov et al. JNS 2014). Applying Bubbles showed that those neurons respond to relatively small stimulus fragments (Popivanov et al. SFN 2013). Here we assess the tolerance of the midSTS body patch neurons to stimulus transformations that preserve shape: changes in retinal location, in size and silhouette and outline rendering of the images (maintaining only shape information, but lacking textural or shading features). Also, we measured the effect of in-plane image rotation. We recorded spiking activity of single neurons from the left midSTS body patch of 2 awake and fixating macaque monkeys. After a search test with 100 stimuli (monkey and human bodies, faces, man-made objects and fruits/vegetables), stimuli were selected for further tests. All stimuli were presented for 200 ms with an inter-stimulus interval of ~ 400 ms. Analyses were done on baseline subtracted firing rates. RF mapping (4º size; 35 locations; 3º steps) showed that the RF of most of the neurons included the fovea. The RFs varied in size (mean > 8º, SD > 3º) and peak location with a bias towards the lower contralateral visual field quadrant. Stimulus preference (5 stimuli; 4º size) was preserved across 2 tested positions inside the RF. Presentations of two stimuli at 2º, 4º or 8º sizes showed strong tolerance of stimulus preference to size changes. Moreover, applications of Bubbles (Popivanov et al. SFN 2013) using two stimulus sizes revealed image fragments at similar relative locations that were correlated across the two sizes, demonstrating size tolerance. To assess whether these neurons still respond selectively when only shape features are present, we showed 10 stimuli in 3 versions: original (shaded and textured), their silhouettes and outlines. The large majority of the neurons responded as well to the silhouette as to the original image and maintained their selectivity for the silhouette versions (median correlation between the responses to the original and the silhouette r = 0.63). Furthermore, the degree of tolerance to the silhouette transformation correlated positively with the body category selectivity (r = 0.35). These data demonstrate that shape features are sufficient to drive body selective neurons of the midSTS body patch. Responses to outlines were reduced and showed less preserved selectivity. In-plane rotation (step: 45º) of the effective stimulus showed that responses of midSTS body patch cells strongly depended on orientation. Keywords: body, Body Shape, temporal cortex, receptive fields, Stimulus Invariance, bubbles Conference: Belgian Brain Council 2014 MODULATING THE BRAIN: FACTS, FICTION, FUTURE, Ghent, Belgium, 4 Oct - 4 Oct, 2014. Presentation Type: Poster Presentation Topic: Basic Neuroscience Citation: Popivanov ID, Jastorff J, Vanduffel W, Schyns PG and Vogels R (2014). Tolerance of macaque middle superior temporal sulcus body patch neurons to shape-preserving stimulus transformations.. Conference Abstract: Belgian Brain Council 2014 MODULATING THE BRAIN: FACTS, FICTION, FUTURE. doi: 10.3389/conf.fnhum.2014.214.00024 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 25 Jun 2014; Published Online: 30 Jun 2014. * Correspondence: Prof. Rufin Vogels, Katolieke Universiteit Leuven, Biomedische Wetenschapen, Leuven, 3000, Belgium, rufin.vogels@kuleuven.be Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Ivo D Popivanov Jan Jastorff Wim Vanduffel Philippe G Schyns Rufin Vogels Google Ivo D Popivanov Jan Jastorff Wim Vanduffel Philippe G Schyns Rufin Vogels Google Scholar Ivo D Popivanov Jan Jastorff Wim Vanduffel Philippe G Schyns Rufin Vogels PubMed Ivo D Popivanov Jan Jastorff Wim Vanduffel Philippe G Schyns Rufin Vogels Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

140 Cognitive Deficits After Traumatic Brain Injury are Associated With Decreased Hippocampal Bursting and Improved With Burst Stimulation of the Fornix

INTRODUCTION: Traumatic brain injury (TBI) can lead to profound deficits of learning and memory that can be a source of considerable morbidity. We investigated hippocampal firing patterns after TBI and the effect of hippocampal theta burst stimulation (TBS) on bursting and cognitive recovery after TBI. METHODS: Twenty-four male Sprague-Dawley rats were used in the study; twelve underwent mild fluid percussion injury (FPI, 1.5 Atm) and were compared to twelve sham-operated rats. Twelve rats (6 TBI, 6 sham) underwent bilateral implantation of electrodes into the CA1 and CA3 hippocampal subfields, and twelve rats (6 TBI, 6 sham) underwent implantation of a stimulating electrode into the fornix. Rats were trained to perform in a delayed nonmatch-to-place swim T-maze. Single neuron busting activity and maze performance were analyzed during task performance 30-90 days after trauma. Theta burst stimulation (TBS, 200 Hz in 50 ms trains, 5 trains per second, 60 μA biphasic pulses) was delivered to the fornix electrodes during task performance in implanted animals. RESULTS: There were no histological differences between control and mTBI rats, and stereological analysis demonstrated no neuronal loss. Rats subjected to mTBI demonstrated significantly poorer performance on the memory task compared with sham rats. Examination of single-neuron spiking activity during exploratory activity revealed that TBI was associated with significantly less hippocampal bursting (P < .05) with a trend toward longer bursts and lower inter-burst spike frequency in the TBI group. Burst stimulation of the fornix normalized cognitive performance in the TBI group to levels indistinguishable from the sham group. CONCLUSION: Deficits in learning and memory after TBI are associated with decreased hippocampal burst activity and are improved with TBS of the hippocampus.

Reward-Modulated Motor Information in Identified Striatum Neurons

It is widely accepted that dorsal striatum neurons participate in either the direct pathway (expressing dopamine D1 receptors) or the indirect pathway (expressing D2 receptors), controlling voluntary movements in an antagonistically balancing manner. The D1- and D2-expressing neurons are activated and inactivated, respectively, by dopamine released from substantia nigra neurons encoding reward expectation. However, little is known about the functional representation of motor information and its reward modulation in individual striatal neurons constituting the two pathways. In this study, we juxtacellularly recorded the spike activity of single neurons in the dorsolateral striatum of rats performing voluntary forelimb movement in a reward-predictable condition. Some of these neurons were identified morphologically by a combination of juxtacellular visualization and in situ hybridization for D1 mRNA. We found that the striatal neurons exhibited distinct functional activations before and during the forelimb movement, regardless of the expression of D1 mRNA. They were often positively, but rarely negatively, modulated by expecting a reward for the correct motor response. The positive reward modulation was independent of behavioral differences in motor performance. In contrast, regular-spiking and fast-spiking neurons in any layers of the motor cortex displayed only minor and unbiased reward modulation of their functional activation in relation to the execution of forelimb movement. Our results suggest that the direct and indirect pathway neurons cooperatively rather than antagonistically contribute to spatiotemporal control of voluntary movements, and that motor information is subcortically integrated with reward information through dopaminergic and other signals in the skeletomotor loop of the basal ganglia.

Signal Multiplexing and Single-Neuron Computations in Lateral Intraparietal Area During Decision-Making

Previous work has revealed a remarkably direct neural correlate of decisions in the lateral intraparietal area (LIP). Specifically, firing rate has been observed to ramp up or down in a manner resembling the accumulation of evidence for a perceptual decision reported by making a saccade into (or away from) the neuron's response field (RF). However, this link between LIP response and decision formation emerged from studies where a saccadic target was always stimulating the RF during decisions, and where the neural correlate was the averaged activity of a restricted sample of neurons. Because LIP cells are (1) highly responsive to the presence of a visual stimulus in the RF, (2) heterogeneous, and (3) not clearly anatomically segregated from large numbers of neurons that fail selection criteria, the underlying neuronal computations are potentially obscured. To address this, we recorded single neuron spiking activity in LIP during a well-studied moving-dot direction-discrimination task and manipulated whether a saccade target was present in the RF during decision-making. We also recorded from a broad sample of LIP neurons, including ones conventionally excluded in prior studies. Our results show that cells multiplex decision signals with decision-irrelevant visual signals. We also observed disparate, repeating response "motifs" across neurons that, when averaged together, resemble traditional ramping decision signals. In sum, neural responses in LIP simultaneously carry decision signals and decision-irrelevant sensory signals while exhibiting diverse dynamics that reveal a broader range of neural computations than previously entertained.

Mapping the spatio-temporal structure of motor cortical LFP and spiking activities during reach-to-grasp movements.

Grasping an object involves shaping the hand and fingers in relation to the object’s physical properties. Following object contact, it also requires a fine adjustment of grasp forces for secure manipulation. Earlier studies suggest that the control of hand shaping and grasp force involve partially segregated motor cortical networks. However, it is still unclear how information originating from these networks is processed and integrated. We addressed this issue by analyzing massively parallel signals from population measures (local field potentials, LFPs) and single neuron spiking activities recorded simultaneously during a delayed reach-to-grasp task, by using a 100-electrode array chronically implanted in monkey motor cortex. Motor cortical LFPs exhibit a large multi-component movement-related potential (MRP) around movement onset. Here, we show that the peak amplitude of each MRP component and its latency with respect to movement onset vary along the cortical surface covered by the array. Using a comparative mapping approach, we suggest that the spatio-temporal structure of the MRP reflects the complex physical properties of the reach-to-grasp movement. In addition, we explored how the spatio-temporal structure of the MRP relates to two other measures of neuronal activity: the temporal profile of single neuron spiking activity at each electrode site and the somatosensory receptive field properties of single neuron activities. We observe that the spatial representations of LFP and spiking activities overlap extensively and relate to the spatial distribution of proximal and distal representations of the upper limb. Altogether, these data show that, in motor cortex, a precise spatio-temporal pattern of activation is involved for the control of reach-to-grasp movements and provide some new insight about the functional organization of motor cortex during reaching and object manipulation.

Modulation of V1 Spike Response by Temporal Interval of Spatiotemporal Stimulus Sequence

The spike activity of single neurons of the primary visual cortex (V1) becomes more selective and reliable in response to wide-field natural scenes compared to smaller stimuli confined to the classical receptive field (RF). However, it is largely unknown what aspects of natural scenes increase the selectivity of V1 neurons. One hypothesis is that modulation by surround interaction is highly sensitive to small changes in spatiotemporal aspects of RF surround. Such a fine-tuned modulation would enable single neurons to hold information about spatiotemporal sequences of oriented stimuli, which extends the role of V1 neurons as a simple spatiotemporal filter confined to the RF. In the current study, we examined the hypothesis in the V1 of awake behaving monkeys, by testing whether the spike response of single V1 neurons is modulated by temporal interval of spatiotemporal stimulus sequence encompassing inside and outside the RF. We used two identical Gabor stimuli that were sequentially presented with a variable stimulus onset asynchrony (SOA): the preceding one (S1) outside the RF and the following one (S2) in the RF. This stimulus configuration enabled us to examine the spatiotemporal selectivity of response modulation from a focal surround region. Although S1 alone did not evoke spike responses, visual response to S2 was modulated for SOA in the range of tens of milliseconds. These results suggest that V1 neurons participate in processing spatiotemporal sequences of oriented stimuli extending outside the RF.

Mild Traumatic Brain Injury Is Associated with Impaired Hippocampal Spatiotemporal Representation in the Absence of Histological Changes

Mild traumatic brain injury (mTBI) accounts for the majority of head trauma cases. Despite some lasting cognitive, emotional, and behavioral deficits, there are frequently no overt morphological defects, suggesting that changes may result from alterations in the physiology of individual neurons. We investigated hippocampal neural activity in rats during a working memory task to determine the effect of mTBI on cellular physiology. Male Sprague-Dawley rats (300-350 g) underwent mTBI via lateral fluid percussion (1.5 atm), and were compared with sham-operated rats. The rats then underwent bilateral implantation of electrodes into the CA1 and CA3 hippocampal subfields and were trained to perform in a delayed nonmatch-to-place swim T-maze. Single-neuron activity was analyzed during task performance 30-90 days after trauma. There were no histological differences between control and mTBI rats. Stereological analysis demonstrated no neuronal loss. Nevertheless, rats subjected to mTBI demonstrated significantly poorer performance on the task with increasing delay. Examination of single-neuron spiking activity revealed no significant difference in firing rates or spike characteristics, but rats exposed to mTBI were found to have significantly fewer cells with activity spatiotemporally correlated with location in the maze ("task-specific cells," p<0.05 by Fisher's exact test). Memory deficits, including disorganized patterns of hippocampal neural activity after mTBI, were seen in rats. Because it is seen in the absence of clear morphological defects, these data suggest that functional impairment after mTBI may result from alterations in the activity of individual neurons.

Integration of bottom-up and top-down signals in visual recognition

Event Abstract Back to Event Integration of bottom-up and top-down signals in visual recognition Julie Blumberg1*, Jonas Bruder1, Daniel Millman2 and Andreas Schulze-Bonhage1 1 University hospital Freiburg, Epilepsy center, Germany 2 Harvard Medical School, Children's Hospital, United States In a collaboration of Harvard Medical School and University hospital Freiburg we study visual perception and memory in the human brain with high spatial and temporal resolution. Subjects are epilepsy patients who are implanted with depth electrodes and/or intracranial surface electrodes to localize the seizure focus for potential surgical resection. In parallel with field potentials we record single neuron spiking activity using microwires inserted in depth electrodes. The goal of this collaborative effort is to understand the interaction and integration of bottom-up and top-down signals through the combination of neurophysiological recordings at high spatial and temporal resolution in the human brain, computational data analysis and modeling. The properties of hierarchical and feed-forward theories of visual recognition provide a quantitative framework to examine information processing in the feedforward path along the ventral stream to account for ultra-rapid complex object recognition. One of the main limitations of these models is that they do not take into account the massive backprojections that convey information from higher cortical areas back to the lower areas. In order to explain everyday visual perception, we need to incorporate a quantitative and computational description of top-down control of sensory processing derived from frontal and parietal cortex as well as medial temporal lobe memory structures. In our study we examine progressively more complex tasks that include both bottom-up and top-down components in order to shed light on the dynamical integration of feed-forward and feed-back signals in the human ventral visual cortex. One type of information that can be fed back is the temporal relationships among visual events in an episodic memory. In order to investigate memory function involved in object recognition, we have subjects perform tasks that involve the learning of image sequences while we record from temporal lobe structures including hippocampus. These tasks offer the potential to reveal functions of the hippocampus in the learning of temporal relationships, such as prospective/anticipatory coding of upcoming images and/or learning of associations among temporally-linked images. In particular, we test the involvement of the hippocampus in learning the temporal component of episodic memories, beyond simple association of the events which are members of the episode. Here, we dissociate the learning of which images are members of a particular sequence from learning of temporal order by asking patients to memorize sequences, then testing either their memory of the sequence members or memory of the temporal relationships among sequence members. Finally, replaying of the order of activation of place cells that together constitute a trajectory to a reward location during and after training occurs in the rodent hippocampus, and is believed to play a role in memory consolidation. We test whether such replay occurs in non-spatial cognitive domains in the human hippocampus. Acknowledgements This work was supported by the NSF/BMBF Award for US-German Collaboration in Computational Neuroscience (Award ID 1010109/01GQ1010). Keywords: single-unit recordings, Epilepsy, Visual Cortex, Feedback, ECoG Conference: Bernstein Conference 2012, Munich, Germany, 12 Sep - 14 Sep, 2012. Presentation Type: Poster Topic: Sensory processing and perception Citation: Blumberg J, Bruder J, Millman D and Schulze-Bonhage A (2012). Integration of bottom-up and top-down signals in visual recognition. Front. Comput. Neurosci. Conference Abstract: Bernstein Conference 2012. doi: 10.3389/conf.fncom.2012.55.00044 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 13 Jul 2012; Published Online: 12 Sep 2012. * Correspondence: Mrs. Julie Blumberg, University hospital Freiburg, Epilepsy center, Freiburg, Germany, julie.blumberg@uniklinik-freiburg.de Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Julie Blumberg Jonas Bruder Daniel Millman Andreas Schulze-Bonhage Google Julie Blumberg Jonas Bruder Daniel Millman Andreas Schulze-Bonhage Google Scholar Julie Blumberg Jonas Bruder Daniel Millman Andreas Schulze-Bonhage PubMed Julie Blumberg Jonas Bruder Daniel Millman Andreas Schulze-Bonhage Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.