Multiunit Spiking Activity Research Articles

Recent Visual Experience Shapes Visual Processing in Rats through Stimulus-Specific Adaptation and Response Enhancement

From an ecological point of view, it is generally suggested that the main goal of vision in rats and mice is navigation and (aerial) predator evasion [1-3]. The latter requires fast and accurate detection of a changein the visual environment. An outstanding question is whether there are mechanisms in the rodent visual system that would support and facilitate visual change detection. An experimental protocol frequently used to investigate change detection in humans is the oddball paradigm, in which a rare, unexpected stimulus is presented in a train of stimulus repetitions [4]. A popular "predictive coding" theory of cortical responses states that neural responses should decrease for expected sensory input and increase for unexpected input [5, 6]. Despite evidence for response suppression and enhancement in noninvasive scalp recordings in humans with this paradigm [7, 8], it has proven challenging to observe both phenomena in invasive action potential recordings in other animals [9-11]. During a visual oddball experiment, we recorded multi-unit spiking activity in rat primary visual cortex (V1) and latero-intermediate area (LI), which is a higher area of the rodent ventral visual stream. In rat V1, there was only evidence for response suppression related to stimulus-specific adaptation, and not for response enhancement. However, higher up in area LI, spiking activity showed clear surprise-based response enhancement in addition to stimulus-specific adaptation. These results show that neural responses along the rat ventral visual stream become increasingly sensitive to changes in the visual environment, suggesting a system specialized in the detection of unexpected events.

Rapid classification of hippocampal replay content for real-time applications

Sharp-wave ripple (SWR) events in the hippocampus replay millisecond-timescale patterns of place cell activity related to the past experience of an animal. Interrupting SWR events leads to learning and memory impairments, but how the specific patterns of place cell spiking seen during SWRs contribute to learning and memory remains unclear. A deeper understanding of this issue will require the ability to manipulate SWR events based on their content. Accurate real-time decoding of SWR replay events requires new algorithms that are able to estimate replay content and the associated uncertainty, along with software and hardware that can execute these algorithms for biological interventions on a millisecond timescale. Here we develop an efficient estimation algorithm to categorize the content of replay from multiunit spiking activity. Specifically, we apply real-time decoding methods to each SWR event and then compute the posterior probability of the replay feature. We illustrate this approach by classifying SWR events from data recorded in the hippocampus of a rat performing a spatial memory task into four categories: whether they represent outbound or inbound trajectories and whether the activity is replayed forward or backward in time. We show that our algorithm can classify the majority of SWR events in a recording epoch within 20 ms of the replay onset with high certainty, which makes the algorithm suitable for a real-time implementation with short latencies to incorporate into content-based feedback experiments.

Spatial Restriction of Neural Activation Using Focused Multipolar Stimulation With a Retinal Prosthesis.

The resolution provided by present state-of-the-art retinal prostheses is severely limiting for recipients, partly due to the broad spread of activation in the retina in response to monopolar (MP) electrical stimulation. Focused multipolar (FMP) stimulation has been shown to restrict neural activation in the cochlea compared to MP stimulation. We extended the FMP stimulation technique to a two-dimensional electrode array and compared its efficacy to MP and hexapolar (HP) stimulation in the retina. Normally-sighted cats (n = 6) were implanted with a suprachoroidal electrode array containing 42 electrodes. Multichannel multiunit spiking activity was recorded from the visual cortex in response to MP, HP, and FMP retinal stimulation. When inferring retinal spread using voltage recordings off the stimulating array, FMP stimulation showed significantly reduced voltages in regions surrounding the primary stimulating electrode. When measuring the retinal and cortical selectivity of neural responses, FMP and HP stimulation showed significantly higher selectivity compared to MP stimulation (separate 2-way ANOVAs, P < 0.05). However, the lowest cortical thresholds for each stimulating electrode were higher for FMP and HP compared to MP stimulation (1-way ANOVA, P < 0.001). No significant differences were observed between FMP and HP stimulation in any measures. Focused multipolar and HP stimulation using a two-dimensional array are promising techniques to reduce the spread of activation for a retinal prosthesis. Clinical application would be expected to result in smaller phosphenes; thus, reducing phosphene overlap between electrodes and increasing the resolution at the expense of higher thresholds for activation.

Multiscale Aspects of Generation of High-Gamma Activity during Seizures in Human Neocortex.

High-gamma (HG; 80-150 Hz) activity in macroscopic clinical records is considered a marker for critical brain regions involved in seizure initiation; it is correlated with pathological multiunit firing during neocortical seizures in the seizure core, an area identified by correlated multiunit spiking and low frequency seizure activity. However, the effects of the spatiotemporal dynamics of seizure on HG power generation are not well understood. Here, we studied HG generation and propagation, using a three-step, multiscale signal analysis and modeling approach. First, we analyzed concurrent neuronal and microscopic network HG activity in neocortical slices from seven intractable epilepsy patients. We found HG activity in these networks, especially when neurons displayed paroxysmal depolarization shifts and network activity was highly synchronized. Second, we examined HG activity acquired with microelectrode arrays recorded during human seizures (n = 8). We confirmed the presence of synchronized HG power across microelectrode records and the macroscale, both specifically associated with the core region of the seizure. Third, we used volume conduction-based modeling to relate HG activity and network synchrony at different network scales. We showed that local HG oscillations require high levels of synchrony to cross scales, and that this requirement is met at the microscopic scale, but not within macroscopic networks. Instead, we present evidence that HG power at the macroscale may result from harmonics of ongoing seizure activity. Ictal HG power marks the seizure core, but the generating mechanism can differ across spatial scales.

Decoding position from multiunit activity using a marked point process filter

Traditionally, experiments designed to study the role of specific spike patterns in learning and memory tasks take one of two forms, 1) observational studies that characterize statistical properties of neural activity during such tasks or 2) interventional studies that broadly alter neural activities over an entire neural population or brain region. This work is part of a larger project to allow investigators to manipulate neural populations in a content-specific way, altering spiking activity related to certain learning and memory patterns while leaving activity related to other patterns intact. One fundamental challenge of this work is to decode the information content of specific spike sequences in real-time. Previously, we have used point process theory to develop efficient decoding algorithms based on spike train observations. However these algorithms assume the spike trains have been accurately sorted ahead of time, which is not possible for real-time decoding. Here we present a new point process decoding algorithm that does not require multiunit signals to be sorted. We use the theory of marked point processes to characterize the relationship between the coding properties of multiunit activity and features of the spike waveforms [1-3]. Using Bayes’ rule, we compute the posterior distribution of a signal to decode given multiunit activity from a neural population. We first characterize the spiking activity of a neural population using the conditional intensity function for marked point processes. We then construct point process filters to iteratively calculate the full posterior density of a signal. We illustrate our approach with a simulation study as well as with experimental data recorded in the hippocampus of a rat performing a spatial memory task. Our decoding framework is used to reconstruct the animal’s position from unsorted multiunit spiking activity. We then compare the quality of fit of our decoding framework to that of a traditional spike-sorting and decoding framework. Our analyses show that the proposed decoding algorithm performs as well as or better than algorithms based on sorted single-unit activity. These results provide a mechanism for content-specific manipulations of population activity in hippocampus.

Clusterless Decoding of Position from Multiunit Activity Using a Marked Point Process Filter.

Point process filters have been applied successfully to decode neural signals and track neural dynamics. Traditionally these methods assume that multiunit spiking activity has already been correctly spike-sorted. As a result, these methods are not appropriate for situations where sorting cannot be performed with high precision, such as real-time decoding for brain-computer interfaces. Because the unsupervised spike-sorting problem remains unsolved, we took an alternative approach that takes advantage of recent insights into clusterless decoding. Here we present a new point process decoding algorithm that does not require multiunit signals to be sorted into individual units. We use the theory of marked point processes to construct a function that characterizes the relationship between a covariate of interest (in this case, the location of a rat on a track) and features of the spike waveforms. In our example, we use tetrode recordings, and the marks represent a four-dimensional vector of the maximum amplitudes of the spike waveform on each of the four electrodes. In general, the marks may represent any features of the spike waveform. We then use Bayes's rule to estimate spatial location from hippocampal neural activity. We validate our approach with a simulation study and experimental data recorded in the hippocampus of a rat moving through a linear environment. Our decoding algorithm accurately reconstructs the rat's position from unsorted multiunit spiking activity. We then compare the quality of our decoding algorithm to that of a traditional spike-sorting and decoding algorithm. Our analyses show that the proposed decoding algorithm performs equivalent to or better than algorithms based on sorted single-unit activity. These results provide a path toward accurate real-time decoding of spiking patterns that could be used to carry out content-specific manipulations of population activity in hippocampus or elsewhere in the brain.

Optogenetic stimulation of the cochlear nucleus using channelrhodopsin-2 evokes activity in the central auditory pathways

Optogenetics has become an important research tool and is being considered as the basis for several neural prostheses. However, few studies have applied optogenetics to the auditory brainstem. This study explored whether optical activation of the cochlear nucleus (CN) elicited responses in neurons in higher centers of the auditory pathway and whether it elicited an evoked response. Viral-mediated gene transfer was used to express channelrhodopsin-2 (ChR2) in the mouse CN. Blue light was delivered via an optical fiber placed near the surface of the infected CN and recordings were made in higher-level centers. Optical stimulation evoked excitatory multiunit spiking activity throughout the tonotopic axis of the central nucleus of the inferior colliculus (IC) and the auditory cortex (Actx). The pattern and magnitude of IC activity elicited by optical stimulation was comparable to that obtained with a 50dB SPL acoustic click. This broad pattern of activity was consistent with histological confirmation of green fluorescent protein (GFP) label of cell bodies and axons throughout the CN. Increasing pulse rates up to 320Hz did not significantly affect threshold or bandwidth of the IC responses, but rates higher than 50Hz resulted in desynchronized activity. Optical stimulation also evoked an auditory brainstem response, which had a simpler waveform than the response to acoustic stimulation. Control cases showed no responses to optical stimulation. These data suggest that optogenetic control of central auditory neurons is feasible, but opsins with faster channel kinetics may be necessary to convey information at rates typical of many auditory signals.

Virtual electrodes by current steering in retinal prostheses.

Retinal prostheses are an approved treatment for vision restoration in retinal degenerative diseases; however, present implants have limited resolution and simply increasing the number of electrodes is limited by design issues. In cochlear implants, virtual electrodes can be created by simultaneous stimulation of adjacent physical electrodes (current steering). The present study assessed whether this type of current steering can be adapted for retinal implants. Suprachoroidal electrode arrays were implanted in four normally sighted cat eyes. Electrode pairs were driven simultaneously at different current levels and current ratios. Multiunit spiking activity in the visual cortex was recorded. Spike distribution across channels enabled generation of cortical activation maps and calculation of centroid positions. For each current configuration, centroid shifts between two virtual electrodes were compared to shifts obtained from physical electrode stimulation. Using current steering, virtual electrodes with different cortical activation maps could be created. Cortical centroids were found to shift as a function of the current ratio used for virtual electrodes and were similar to the centroid shifts seen when using physical electrodes. In addition, the cortical response to stimulation of a physical electrode could be reproduced by applying current steering to electrodes on either side of the physical electrode. These results suggest that current steering can alter activation patterns in the visual cortex and could enhance visual perception in retinal implants by eliciting phosphene percepts intermediate between those elicited by physical electrodes. These results inform development of new electrode arrays that can take advantage of current steering.

Binocular flash suppression in the primary visual cortex of anesthetized and awake macaques.

Primary visual cortex (V1) was implicated as an important candidate for the site of perceptual suppression in numerous psychophysical and imaging studies. However, neurophysiological results in awake monkeys provided evidence for competition mainly between neurons in areas beyond V1. In particular, only a moderate percentage of neurons in V1 were found to modulate in parallel with perception with magnitude substantially smaller than the physical preference of these neurons. It is yet unclear whether these small modulations are rooted from local circuits in V1 or influenced by higher cognitive states. To address this question we recorded multi-unit spiking activity and local field potentials in area V1 of awake and anesthetized macaque monkeys during the paradigm of binocular flash suppression. We found that a small but significant modulation was present in both the anesthetized and awake states during the flash suppression presentation. Furthermore, the relative amplitudes of the perceptual modulations were not significantly different in the two states. We suggest that these early effects of perceptual suppression might occur locally in V1, in prior processing stages or within early visual cortical areas in the absence of top-down feedback from higher cognitive stages that are suppressed under anesthesia.

Contralateral dissociation between neural activity and cerebral blood volume during recurrent acute focal neocortical seizures.

ObjectiveWhether epileptic events disrupt normal neurovascular coupling mechanisms locally or remotely is unclear. We sought to investigate neurovascular coupling in an acute model of focal neocortical epilepsy, both within the seizure onset zone and in contralateral homotopic cortex.MethodsNeurovascular coupling in both ipsilateral and contralateral vibrissal cortices of the urethane-anesthetized rat were examined during recurrent 4-aminopyridine (4-AP, 15 mm, 1 μl) induced focal seizures. Local field potential (LFP) and multiunit spiking activity (MUA) were recorded via two bilaterally implanted 16-channel microelectrodes. Concurrent two-dimensional optical imaging spectroscopy was used to produce spatiotemporal maps of cerebral blood volume (CBV).ResultsRecurrent acute seizures in right vibrissal cortex (RVC) produced robust ipsilateral increases in LFP and MUA activity, most prominently in layer 5, that were nonlinearly correlated to local increases in CBV. In contrast, contralateral left vibrissal cortex (LVC) exhibited relatively smaller nonlaminar specific increases in neural activity coupled with a decrease in CBV, suggestive of dissociation between neural and hemodynamic responses.SignificanceThese findings provide insights into the impact of epileptic events on the neurovascular unit, and have important implications both for the interpretation of perfusion-based imaging signals in the disorder and understanding the widespread effects of epilepsy.

Non-invasive detection of cortical population spikes: Functional discrimination of pre- vs. postsynaptic components in SEP at 1 kHz

Introduction: Ultrafast EEG signals, featuring frequencies above 500 Hz, can be observed in scalp somatosensory evoked potentials (SEP). Usually, these recordings have a low Signal-to-Noise Ratio (SNR) because weak signals are overlaid by intrinsic noise of much higher amplitude as generated by biological sources and the amplifier. Scalp recordings of SEP show bursts above 400 Hz with submicro-volt amplitudes, which could be extracted from noise up to now only by the use of massive averaging (n > 1000) and digital signal processing. Methods: Here, we investigate SEP up to 1 kHz elicited by median nerve stimulation with rates of either 0.99 Hz or 8.1 Hz. We exploit the increased SNR provided by a custom-made low noise amplifier technology together with an adapted implementation of Canonical Correlation Analyis algorithm, based on the assumption of high level stimulus phase locking across trials. Results: It proved possible in 3/3 subjects to discriminate hf-SEP generators at subcortical and intracortical levels at the single trial level, relying on the different neuronal refractory properties of these components which are phase-locked to the stimulus onset. Discussion: A custom-made low-noise EEG system enables the noninvasive detection of pre- and postsynaptic evoked activity at 1 kHz, i.e., in the frequency range housing spike-related multi-unit activity in intracortical recordings, providing the opportunity of non-invasive monitoring of multi-unit spike activity in man.

Effect of Adaptation on Object Representation Accuracy in Macaque Inferior Temporal Cortex

Stimulus repetition produces a decrease of the response in many cortical areas and different modalities. This adaptation is highly prominent in macaque inferior temporal (IT) neurons. Here we ask how these repetition-induced changes in IT responses affect the accuracy by which IT neurons encode objects. This question bears on the functional consequences of adaptation, which are still unclear. We recorded the responses of single IT neurons to sequences of familiar shapes, each shown for 300 msec with an ISI of the same duration. The difference in shape between the two successively presented stimuli,that is, adapter and test, varied parametrically. The discriminability of the test stimuli was reduced for repeated compared with nonrepeated stimuli. In some conditions for which adapter and test shapes differed, the cross-adaptation resulted in an enhanced discriminability. These single cell results were confirmed in a second experiment in which we recorded multiunit spiking activity using a laminar microelectrode in macaque IT. Two familiar stimuli were presented successively for 500 msec each and separated with an ISI of the same duration. Trials consisted either of a repetition of the same stimulus or of their alternation. Small neuronal populations showed decreased classification accuracy for repeated compared with nonrepeated test stimuli, but classification was enhanced for the test compared with adapter stimuli when the test stimulus differed from recently seen stimuli. These findings suggest that short-term, stimulus-specific adaptation in IT supports efficient coding of stimuli that differ from recently seen ones while impairing the coding of repeated stimuli.

Auditory Cortex Represents Both Pitch Judgments and the Corresponding Acoustic Cues

SummaryThe neural processing of sensory stimuli involves a transformation of physical stimulus parameters into perceptual features, and elucidating where and how this transformation occurs is one of the ultimate aims of sensory neurophysiology. Recent studies have shown that the firing of neurons in early sensory cortex can be modulated by multisensory interactions [1–5], motor behavior [1, 3, 6, 7], and reward feedback [1, 8, 9], but it remains unclear whether neural activity is more closely tied to perception, as indicated by behavioral choice, or to the physical properties of the stimulus. We investigated which of these properties are predominantly represented in auditory cortex by recording local field potentials (LFPs) and multiunit spiking activity in ferrets while they discriminated the pitch of artificial vowels. We found that auditory cortical activity is informative both about the fundamental frequency (F0) of a target sound and also about the pitch that the animals appear to perceive given their behavioral responses. Surprisingly, although the stimulus F0 was well represented at the onset of the target sound, neural activity throughout auditory cortex frequently predicted the reported pitch better than the target F0.

Non-invasive detection of cortical population spikes: Functional discrimination of pre- vs. postsynaptic components in SEP at 1 kHz

Introduction: Ultrafast EEG signals, featuring frequencies above 500 Hz, can be observed in scalp somatosensory evoked potentials (SEP). Usually, these recordings have a low Signal-to-Noise Ratio (SNR) because weak signals are overlaid by intrinsic noise of much higher amplitude as generated by biological sources and the amplifier. Scalp recordings of SEP show bursts above 400 Hz with submicro-volt amplitudes, which could be extracted from noise up to now only by the use of massive averaging (n > 1000) and digital signal processing. Methods: Here, we investigate SEP up to 1 kHz elicited by median nerve stimulation with rates of either 0.99 Hz or 8.1 Hz. We exploit the increased SNR provided by a custom-made low noise amplifier technology together with an adapted implementation of Canonical Correlation Analyis algorithm, based on the assumption of high level stimulus phase locking across trials. Results: It proved possible in 3/3 subjects to discriminate hf-SEP generators at subcortical and intracortical levels at the single trial level, relying on the different neuronal refractory properties of these components which are phase-locked to the stimulus onset. Discussion: A custom-made low-noise EEG system enables the noninvasive detection of pre- and postsynaptic evoked activity at 1 kHz, i.e., in the frequency range housing spike-related multi-unit activity in intracortical recordings, providing the opportunity of non-invasive monitoring of multi-unit spike activity in man.

Laminar analysis of visually evoked activity in the primary visual cortex

Studying the laminar pattern of neural activity is crucial for understanding the processing of neural signals in the cerebral cortex. We measured neural population activity [multiunit spike activity (MUA) and local field potential, LFP] in Macaque primary visual cortex (V1) in response to drifting grating stimuli. Sustained visually driven MUA was at an approximately constant level across cortical depth in V1. However, sustained, visually driven, local field potential power, which was concentrated in the γ-band (20-60 Hz), was greatest at the cortical depth corresponding to cortico-cortical output layers 2, 3, and 4B. γ-band power also tends to be more sustained in the output layers. Overall, cortico-cortical output layers accounted for 67% of total γ-band activity in V1, whereas 56% of total spikes evoked by drifting gratings were from layers 2, 3, and 4B. The high-resolution layer specificity of γ-band power, the laminar distribution of MUA and γ-band activity, and their dynamics imply that neural activity in V1 is generated by laminar-specific mechanisms. In particular, visual responses of MUA and γ-band activity in cortico-cortical output layers 2, 3, and 4B seem to be strongly influenced by laminar-specific recurrent circuitry and/or feedback.

Towards non-invasive multi-unit spike recordings: Mapping 1 kHz EEG signals over human somatosensory cortex

ObjectiveScalp-derived human somatosensory evoked potentials (SEPs) contain high-frequency oscillations (600Hz; ‘sigma-burst’) reflecting concomitant bursts of spike responses in primary somatosensory cortex that repeat regularly at 600Hz. Notably, recent human intracranial SEP have revealed also 1kHz responses (‘kappa-burst’), possibly reflecting non-rhythmic spiking summed over multiple cells (MUA: multi-unit activity). However, the non-invasive detection of EEG signals at 1kHz typical for spikes has always been limited by noise contributions from both, amplifier and body/electrode interface. Accordingly, we developed a low-noise recording set-up optimised to map non-invasively 1kHz SEP components. MethodsSEP were recorded upon 4Hz left median nerve stimulation in 6 healthy human subjects. Scalp potentials were acquired inside an electrically and magnetically shielded room using low-noise custom-made amplifiers. Furthermore, in order to reduce thermal Johnson noise contributions from the sensor/skin interface, electrode impedances were adjusted to ⩽1kΩ. Responses averaged after repeated presentation of the stimulus (n=4000 trials) were evaluated by spatio-temporal pattern analyses in complementary spectral bands. ResultsThree distinct spectral components were identified: N20 (<100Hz), sigma-burst (450–750Hz), and kappa-burst (850–1200Hz). The two high-frequency bursts (sigma, kappa) exhibited distinct and partially independent spatiotemporal evolutions, indicating subcortical as well as several cortical generators. ConclusionsUsing a dedicated low-noise set-up, human SEP ‘kappa-bursts’ at 1kHz can be non-invasively detected and their scalp distribution be mapped. Their topographies indicate a set of subcortical/cortical generators, at least partially distinct from the topography of the 600Hz sigma-bursts described previously. SignificanceThe non-invasive detection and surface mapping of 1kHz EEG signals presented here provides an essential step towards non-invasive monitoring of multi-unit spike activity.

Stimulus repetition affects both strength and synchrony of macaque inferior temporal cortical activity

Repetition of a visual stimulus reduces the firing rate of macaque inferior temporal (IT) neurons. The neural mechanisms underlying this adaptation or repetition suppression are still unclear. In particular, we do not know how the IT circuit is affected by stimulus repetition. To address this, we measured local field potentials (LFPs) and multiunit spiking activity (MUA) simultaneously at 16 sites with a laminar electrode in IT while repeating visual images. Stimulus exposures and interstimulus intervals were each 500 ms. The rhesus monkeys were performing a passive fixation task during the recordings. Induced LFP power decreased with repetition for spectral frequencies above 60 Hz but increased with repetition for lower frequencies, the latter because of a delayed decrease in power when repeating a stimulus. LFP-LFP and MUA-LFP coherences decreased with repetition for frequencies above 60 Hz. This repetition suppression of the MUA-LFP coherence was not due to differences in firing rate since it was present when spike counts were equated for the adapter and repeated stimuli. For frequencies between 15 and 40 Hz, the effect of repetition on synchronization depended on the electrode depth: For the putative superficial layers synchronization was enhanced with repetition, while the LFPs of the putative deep layers decreased their synchrony across layers. The between-site, trial-to-trial covariations in MUA ("noise correlations") decreased with repetition, but this might have reflected repetition suppression of the firing rate. This work demonstrates that short-term stimulus repetition affects the synchronized activity, in addition to response strength, in IT cortex.

Yesterday's noise may be tomorrow's signal: Where are today's limits for high-resolution high-frequency surface EEG?

Recent intracranial EEG recordings revealed that frequencies above 100 Hz convey signals highly informative for application scenarios as diverse as movement decoding for Brain-Computer Interfaces and focus localization in cases with neocortical epilepsies. While such novel concepts are advancing rapidly, they still rely on technology that has been optimised for the conventional, i.e., low-frequency (&lt; 100 Hz), EEG. However, such clinical routine recordings are compromised by a progressively decreasing signal-to-noise ratio for higher frequencies; in particular, the non-invasive detection of scalp EEG signals at 1 kHz typical for spikes has always been limited by noise contributions from both, amplifier and body/electrode interface. Accordingly, we developed a low-noise recording set-up optimised to map high-frequency EEG and employed it for the analysis of median nerve SEP components which provide an opportunity to monitor non-invasively the timing of population spikes in the human cerebral somatosensory system. 28-channel SEP were recorded using custom-made amplifiers featuring an intrinsically low white-noise level. Furthermore, in order to reduce thermal Johnson noise contributions from the sensor/skin interface, electrode impedances were adjusted to &lt; 1 kOhm. Based on this tailored approach a high-frequency SEP-component with its main energy at about 1 kHz was identified non-invasively which exhibited a distinct spatiotemporal evolution indicating subcortical as well as several cortical generators. Thus, augmenting the standard low-frequency SEP, the surface mapping of 1 kHz EEG signals may represent an essential step towards non-invasive monitoring of multi-unit spike activity.

Gamma Oscillations Are Generated Locally in an Attention-Related Midbrain Network

Gamma-band (25-140 Hz) oscillations are a hallmark of sensory processing in the forebrain. The optic tectum (OT), a midbrain structure implicated in sensorimotor processing and attention, also exhibits gamma oscillations. However, the origin and mechanisms of these oscillations remain unknown. We discovered that in acute slices of the avian OT, persistent (>100 ms) epochs of large amplitude gamma oscillations can be evoked that closely resemble those recorded in vivo. We found that cholinergic, glutamatergic, and GABAergic mechanisms differentially regulate the structure of the oscillations at various timescales. These persistent oscillations originate in the multisensory layers of the OT and are broadcast to visual layers via the cholinergic nucleus Ipc, providing a potential mechanism for enhancing the processing of visual information within the OT. The finding that the midbrain contains an intrinsic gamma-generating circuit suggests that the OT could use its own oscillatory code to route signals to forebrain networks.

Evolution of the Dynamic Changes in Functional Cerebral Oxidative Metabolism from Tissue Mitochondria to Blood Oxygen

The dynamic properties of the cerebral metabolic rate of oxygen consumption (CMR(O2)) during changes in brain activity remain unclear. Therefore, the spatial and temporal evolution of functional increases in CMR(O2) was investigated in the rat somato-sensory cortex during forelimb stimulation under a suppressed blood flow response condition. Temporally, stimulation elicited a fast increase in tissue mitochondria CMR(O2) described by a time constant of ~1 second measured using flavoprotein autofluorescence imaging. CMR(O2)-driven changes in the tissue oxygen tension measured using an oxygen electrode and blood oxygenation measured using optical imaging of intrinsic signal followed; however, these changes were slow with time constants of ~5 and ~10 seconds, respectively. This slow change in CMR(O2)-driven blood oxygenation partly explains the commonly observed post-stimulus blood oxygen level-dependent (BOLD) undershoot. Spatially, the changes in mitochondria CMR(O2) were similar to the changes in blood oxygenation. Finally, the increases in CMR(O2) were well correlated with the evoked multi-unit spiking activity. These findings show that dynamic CMR(O2) calculations made using only blood oxygenation data (e.g., BOLD functional magnetic resonance imaging (fMRI)) do not directly reflect the temporal changes in the tissue's mitochondria metabolic rate; however, the findings presented can bridge the gap between the changes in cellular oxidative rate and blood oxygenation.