Background Neural Activity Research Articles

Goal-directed action preparation in humans entails a mixture of corticospinal neural computations.

The seemingly effortless ability of humans to transition from thinking about actions to initiating them relies on sculpting corticospinal output from primary motor cortex. This study tested whether canonical additive and multiplicative neural computations, well-described in sensory systems, generalize to the corticospinal pathway during human action preparation. We used non-invasive brain stimulation to measure corticospinal input-output across varying action preparation contexts during instructed-delay finger response tasks. Goal-directed action preparation was marked by increased multiplicative gain of corticospinal projections to task-relevant muscles and additive suppression of corticospinal projections to non-selected and task-irrelevant muscles. Individuals who modulated corticospinal gain to a greater extent were faster to initiate prepared responses. Our findings provide physiological evidence of combined additive suppression and gain modulation in the human motor system. We propose these computations support action preparation by enhancing the contrast between selected motor representations and surrounding background activity to facilitate response selection and execution.

Detection of evoked resonant neural activity in Parkinson's disease.

Objective. This study investigated a machine-learning approach to detect the presence of evoked resonant neural activity (ERNA) recorded during deep brain stimulation (DBS) of the subthalamic nucleus (STN) in people with Parkinson's disease.Approach. Seven binary classifiers were trained to distinguish ERNA from the background neural activity using eight different time-domain signal features.Main results. Nested cross-validation revealed a strong classification performance of 99.1% accuracy, with 99.6% specificity and 98.7% sensitivity to detect ERNA. Using a semi-simulated ERNA dataset, the results show that a signal-to-noise ratio of 15 dB is required to maintain a 90% classifier sensitivity. ERNA detection is feasible with an appropriate combination of signal processing, feature extraction and classifier. Future work should consider reducing the computational complexity for use in real-time applications.Significance. The presence of ERNA can be used to indicate the location of a DBS electrode array during implantation surgery. The confidence score of the detector could be useful for assisting clinicians to adjust the position of the DBS electrode array inside/outside the STN.

Resting-state background features demonstrate multidien cycles in long-term EEG device recordings

BackgroundLongitudinal EEG recorded by implanted devices is critical for understanding and managing epilepsy. Recent research reports patient-specific, multi-day cycles in device-detected epileptiform events that coincide with increased likelihood of clinical seizures. Understanding these cycles could elucidate mechanisms generating seizures and advance drug and neurostimulation therapies. Objective/hypothesisWe hypothesize that seizure-correlated cycles are present in background neural activity, independent of interictal epileptiform spikes, and that neurostimulation may temporarily interrupt these cycles. MethodsWe analyzed regularly-recorded seizure-free data epochs from 20 patients implanted with a responsive neurostimulation (RNS) device for at least 1.5 years, to explore the relationship between cycles in device-detected interictal epileptiform activity (dIEA), clinician-validated interictal spikes, background EEG features, and neurostimulation. ResultsBackground EEG features tracked the cycle phase of dIEA in all patients (AUC: 0.63 [0.56–0.67]) with a greater effect size compared to clinically annotated spike rate alone (AUC: 0.55 [0.53–0.61], p < 0.01). After accounting for circadian variation and spike rate, we observed significant population trends in elevated theta and beta band power and theta and alpha connectivity features at the cycle peaks (sign test, p < 0.05). In the period directly after stimulation we observe a decreased association between cycle phase and EEG features compared to background recordings (AUC: 0.58 [0.55–0.64]). ConclusionsOur findings suggest that seizure-correlated dIEA cycles are not solely due to epileptiform discharges but are associated with background measures of brain state; and that neurostimulation may temporarily interrupt these cycles. These results may help elucidate mechanisms underlying seizure generation, provide new biomarkers for seizure risk, and facilitate monitoring, treating, and managing epilepsy with implantable devices.

Cross-Subject EEG Channel Selection Method for Lower Limb Brain-Computer Interface

Article Cross-Subject EEG Channel Selection Method for Lower Limb Brain-Computer Interface Mingnan Wei 1,2, Mengjie Huang 3,*, and Jiaying Ni 3 1 School of Advanced Technology, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, China 2 Department of Computer Science, University of Liverpool, Liverpool, L69 3BX, United Kingdom 3 Design School, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, China * Correspondence: Mengjie.Huang@xjtlu.edu.cn Received: 27 April 2023 Accepted: 30 June 2023 Published: 26 September 2023 Abstract: Lower limb motor imagery (MI) classification is a challenging research topic in the area of brain-computer interfaces (BCIs), and entails numerous signal channels to provide sufficient information about the background neural activity. However, practical applications often lack the environment to accommodate excessive channels due to the time-consuming setup process, inconvenient movement, and restricted application scenarios. The existing channel selection algorithms (designed for the individual subject) place a great deal of focus on the classified performance comparisons, whereas the significance of actual locations and neural functions of brain regions is disregarded. Although these algorithms require significant computation resources, their selected solutions cannot be re-used for other subjects to realize the cross-subject channel selection and improve the reusability of model due to poor interpretability and inapplicability. To date, there have been no investigations about the cross-subject channel selection problem for the lower limb MI stepping tasks. This study proposes an optimal cross-subject lower limb channel selection that selectively retains significant channels, narrows the computation scope of the selection, and obtains the optimal selection solutions. Through stepping-based MI experiments, the proposed optimal channel selection enables effective recognition in low-channel settings, thereby contributing a lot to the development of generic and convenient lower limb BCI systems. Additionally, statistical analysis reveals a significant difference in energy spectrum between left and right stepping-based MI tasks in the and bands of the frontal lobe channels, providing new evidence that the frontal lobe dramatically affects lower limb MI tasks.

Pulsation artifact removal from intra-operatively recorded local field potentials using sparse signal processing and data-specific dictionary.

Neural recordings frequently get contaminated by ECG or pulsation artifacts. These large amplitude components can mask the neural patterns of interest and make the visual inspection process difficult. The current study describes a sparse signal representation strategy that targets to denoise pulsation artifacts in local field potentials (LFPs) recorded intraoperatively. To estimate the morphology of the artifact, we first detect the QRS-peaks from the simultaneously recorded ECG trace as an anchor point. After the LFP data has been epoched with respect to each beat, a pool of raw data segments of a specific length is generated. Using the K-singular value decomposition (K-SVD) algorithm, we constructed a data-specific dictionary to represent each contaminated LFP epoch in a sparse fashion. Since LFP is aligned to each QRS complex and the background neural activity is uncorrelated to the anchor points, we assumed that constructed dictionary will be formed to mainly represent the pulsation artifact. In this scheme, we performed an orthogonal matching pursuit to represent each LFP epoch as a linear combination of the dictionary atoms. The denoised LFP data is thus obtained by calculating the residual between the raw LFP and its approximation. We discuss and demonstrate the improvements in denoised data and compare the results with respect to principal component analysis (PCA). We noted that there is a comparable change in the signal for visual inspection to observe various oscillating patterns in the alpha and beta bands. We also see a noticeable compression of signal strength in the lower frequency band (<13 Hz), which was masked by the pulsation artifact, and a strong increase in the signal-to-noise ratio (SNR) in the denoised data.Clinical Relevance- Pulsation artifact can mask relevant neural activity patterns and make their visual inspection difficult. Using sparse signal representation, we established a new approach to reconstruct the quasiperiodic pulsation template and computed the residue signal to achieve noise-free neural activity.

Effects of motor cortex neuromodulation on the specificity of corticospinal tract spinal axon outgrowth and targeting in rats

BackgroundNeural activity helps construct neural circuits during development and this function is leveraged by neuromodulation protocols to promote connectivity and repair in maturity. Neuromodulation targeting the motor cortex (MCX) strengthens connections for evoking muscle contraction (MEPs). Mechanisms include promoting local MCX and corticospinal tract (CST) synaptic efficacy and also axon terminal structural changes. ObjectiveIn this study, we address the question of potential causality between neuronal activation and the neuronal structural response. MethodsWe used patterned optogenetic activation (ChR2-EYFP), daily for 10-days, to deliver intermittent theta burst stimulation (iTBS) to activate MCX neurons within the forelimb representation in healthy rats, while differentiating them from neurons in the same population that were not activated. We used chemogenetic DREADD activation to produce a daily period of non-patterned neuronal activation. ResultsWe found a significant increase in CST axon length, axon branching, contacts targeted to a class of premotor interneuron (Chx10), as well as projections into the motor pools in the ventral horn in optically activated but not neighboring non-activated neurons. A period of 2-h of continuous activation daily for 10 days using DREADD chemogenetic activation with systemic clozapine N-oxide (CNO) administration also increased CST axon length and branching, but not the ventral horn and Chx10 targeting effects. Both patterned optical and chemogenetic activation reduced MCX MEP thresholds. ConclusionOur findings show that targeting of CST axon sprouting is dependent on patterned activation, but that CST spinal axon outgrowth and branching are not. Our optogenetic findings, by distinguishing optically activated and non-activated CST axons, suggests that the switch for activity-dependent axonal outgrowth is neuron-intrinsic.

Region-Level Functional and Effective Network Analysis of Human Brain During Cognitive Task Engagement.

Mental disorders are a major source of disability, with few effective treatments. It has recently been argued that these diseases might be effectively treated by focusing on decision-making, and specifically remediating decision-making deficits that act as “ingredients” in these disorders. Prior work showed that direct electrical brain stimulation can enhance human cognitive control, and consequently decision-making. This raises a challenge of detecting cognitive control lapses directly from electrical brain activity. Here, we demonstrate approaches to overcome that challenge. We propose a novel method, referred to as maximal variance node merging (MVNM), that merges nodes within a brain region to construct informative inter-region brain networks. We employ this method to estimate functional (correlational) and effective (causal) networks using local field potentials (LFP) during a cognitive behavioral task. The effective networks computed using convergent cross mapping differentiate task engagement from background neural activity with 85% median classification accuracy. We also derive task engagement networks (TENs): networks that constitute the most discriminative inter-region connections. Subsequent graph analysis illustrates the crucial role of the dorsolateral prefrontal cortex (dlPFC) in task engagement, consistent with a widely accepted model for cognition. We also show that task engagement is linked to prefrontal cortex theta (4-8 Hz) oscillations. We, therefore, identify objective biomarkers associated with task engagement. These approaches may generalize to other cognitive functions, forming the basis of a network-based approach to detecting and rectifying decision deficits.

Epilepsy in Leigh Syndrome With Mitochondrial DNA Mutations.

Background: Leigh syndrome is a mitochondrial cytopathy that presents as a neurodegenerative disease with apparent manifestation in the central nervous system. The aim of the present study was to describe its dominant neurological clinical features and analyze data related to epilepsy in Leigh syndrome accompanied by a mitochondrial DNA mutation.Methods: Whole mitochondrial sequencing was performed on 125 patients clinically suspected of Leigh syndrome. Among them, 25 patients were identified to have mitochondrial DNA associated Leigh syndrome. Electroencephalography (EEG) findings, semiology, brain imaging findings, and biochemical results, were evaluated. We also compared brain magnetic resonance imaging findings and biochemical features in patients with Leigh syndrome based on the presence of epilepsy.Results: Clinical seizures were observed in 14 out of 25 enrolled patients (56%), with focal seizures being the most common type (6/14, 42.8%). All patients were found to have slow and disorganized background neural activity while eight exhibited epileptic discharges on EEG. Mutations at base pairs 10,191 and 8,993 were revealed in a relatively larger number of patients of Leigh syndrome with epilepsy. The presence of gastrointestinal symptoms was significantly more frequent in the epilepsy group (P = 0.042). Diffuse cerebral atrophy was significantly increased (P = 0.042) and cortex signal abnormalities were also increased (P = 0.033) in the epilepsy group.Conclusions: Patients with Leigh syndrome and mitochondrial DNA mutations had a high proportion of central nervous system comorbidities, though the prevalence of epilepsy in this population was not particularly high. Various types of seizure and EEG findings are common in those with Leigh syndrome. Future imaging studies involving more patients and proper mitochondrial DNA mutation analyses are needed to further evaluate the natural course of Leigh syndrome with epilepsy.

A Neural Circuit Mechanism for the Involvements of Dopamine in Effort-Related Choices: Decay of Learned Values, Secondary Effects of Depletion, and Calculation of Temporal Difference Error.

Dopamine has been suggested to be crucially involved in effort-related choices. Key findings are that dopamine depletion (i) changed preference for a high-cost, large-reward option to a low-cost, small-reward option, (ii) but not when the large-reward option was also low-cost or the small-reward option gave no reward, (iii) while increasing the latency in all the cases but only transiently, and (iv) that antagonism of either dopamine D1 or D2 receptors also specifically impaired selection of the high-cost, large-reward option. The underlying neural circuit mechanisms remain unclear. Here we show that findings i–iii can be explained by the dopaminergic representation of temporal-difference reward-prediction error (TD-RPE), whose mechanisms have now become clarified, if (1) the synaptic strengths storing the values of actions mildly decay in time and (2) the obtained-reward-representing excitatory input to dopamine neurons increases after dopamine depletion. The former is potentially caused by background neural activity–induced weak synaptic plasticity, and the latter is assumed to occur through post-depletion increase of neural activity in the pedunculopontine nucleus, where neurons representing obtained reward exist and presumably send excitatory projections to dopamine neurons. We further show that finding iv, which is nontrivial given the suggested distinct functions of the D1 and D2 corticostriatal pathways, can also be explained if we additionally assume a proposed mechanism of TD-RPE calculation, in which the D1 and D2 pathways encode the values of actions with a temporal difference. These results suggest a possible circuit mechanism for the involvements of dopamine in effort-related choices and, simultaneously, provide implications for the mechanisms of TD-RPE calculation.

Characterization of a thalamic nucleus mediating habenula responses to changes in ambient illumination

BackgroundNeural activity in the vertebrate habenula is affected by ambient illumination. The nucleus that links photoreceptor activity with the habenula is not well characterized. Here, we describe the location, inputs and potential function of this nucleus in larval zebrafish.ResultsHigh-speed calcium imaging shows that light ON and OFF both evoke a rapid response in the dorsal left neuropil of the habenula, indicating preferential targeting of this neuropil by afferents conveying information about ambient illumination. Injection of a lipophilic dye into this neuropil led to bilateral labeling of a nucleus in the anterior thalamus that responds to light ON and OFF, and that receives innervation from the retina and pineal organ. Lesioning the neuropil of this thalamic nucleus reduced the habenula response to light ON and OFF. Optogenetic stimulation of the thalamus with channelrhodopsin-2 caused depolarization in the habenula, while manipulation with anion channelrhodopsins inhibited habenula response to light and disrupted climbing and diving evoked by illumination change.ConclusionsA nucleus in the anterior thalamus of larval zebrafish innervates the dorsal left habenula. This nucleus receives input from the retina and pineal, responds to increase and decrease in ambient illumination, enables habenula responses to change in irradiance, and may function in light-evoked vertical migration.

Canonical Cortical Circuit Model Explains Rivalry, Intermittent Rivalry, and Rivalry Memory.

It has been shown that the same canonical cortical circuit model with mutual inhibition and a fatigue process can explain perceptual rivalry and other neurophysiological responses to a range of static stimuli. However, it has been proposed that this model cannot explain responses to dynamic inputs such as found in intermittent rivalry and rivalry memory, where maintenance of a percept when the stimulus is absent is required. This challenges the universality of the basic canonical cortical circuit. Here, we show that by including an overlooked realistic small nonspecific background neural activity, the same basic model can reproduce intermittent rivalry and rivalry memory without compromising static rivalry and other cortical phenomena. The background activity induces a mutual-inhibition mechanism for short-term memory, which is robust to noise and where fine-tuning of recurrent excitation or inclusion of sub-threshold currents or synaptic facilitation is unnecessary. We prove existence conditions for the mechanism and show that it can explain experimental results from the quartet apparent motion illusion, which is a prototypical intermittent rivalry stimulus.

Could transcranial direct current stimulation have unexpected additional benefits in the treatment of depressed patients?

The application of novel brain stimulation techniques to treat depression, and pos-sibly other neuropsychiatric disorders, is a new and rapidly growing field. Among these techniques, transcranial direct cur-rent stimulation (tDCS) is emerging as one of the most promising approaches because of its relative ease of use, safety and neurobiological effects. tDCS involves the use of weak electric currents (1–2 mA), passed through brain tissue via electrodes placed on the scalp. The stimulation is too weak to directly cause neuronal firing, but is thought to interact with the neuronal membrane and background neural activ-ity, resulting in modification of synaptic strength

Neurons Controlling Aplysia Feeding Inhibit Themselves by Continuous NO Production

BackgroundNeural activity can be affected by nitric oxide (NO) produced by spiking neurons. Can neural activity also be affected by NO produced in neurons in the absence of spiking?Methodology/Principal FindingsApplying an NO scavenger to quiescent Aplysia buccal ganglia initiated fictive feeding, indicating that NO production at rest inhibits feeding. The inhibition is in part via effects on neurons B31/B32, neurons initiating food consumption. Applying NO scavengers or nitric oxide synthase (NOS) blockers to B31/B32 neurons cultured in isolation caused inactive neurons to depolarize and fire, indicating that B31/B32 produce NO tonically without action potentials, and tonic NO production contributes to the B31/B32 resting potentials. Guanylyl cyclase blockers also caused depolarization and firing, indicating that the cGMP second messenger cascade, presumably activated by the tonic presence of NO, contributes to the B31/B32 resting potential. Blocking NO while voltage-clamping revealed an inward leak current, indicating that NO prevents this current from depolarizing the neuron. Blocking nitrergic transmission had no effect on a number of other cultured, isolated neurons. However, treatment with NO blockers did excite cerebral ganglion neuron C-PR, a command-like neuron initiating food-finding behavior, both in situ, and when the neuron was cultured in isolation, indicating that this neuron also inhibits itself by producing NO at rest.Conclusion/SignificanceSelf-inhibitory, tonic NO production is a novel mechanism for the modulation of neural activity. Localization of this mechanism to critical neurons in different ganglia controlling different aspects of a behavior provides a mechanism by which a humeral signal affecting background NO production, such as the NO precursor L-arginine, could control multiple aspects of the behavior.

Emergence of Resonances in Neural Systems: The Interplay between Adaptive Threshold and Short-Term Synaptic Plasticity

In this work we study the detection of weak stimuli by spiking (integrate-and-fire) neurons in the presence of certain level of noisy background neural activity. Our study has focused in the realistic assumption that the synapses in the network present activity-dependent processes, such as short-term synaptic depression and facilitation. Employing mean-field techniques as well as numerical simulations, we found that there are two possible noise levels which optimize signal transmission. This new finding is in contrast with the classical theory of stochastic resonance which is able to predict only one optimal level of noise. We found that the complex interplay between adaptive neuron threshold and activity-dependent synaptic mechanisms is responsible for this new phenomenology. Our main results are confirmed by employing a more realistic FitzHugh-Nagumo neuron model, which displays threshold variability, as well as by considering more realistic stochastic synaptic models and realistic signals such as poissonian spike trains.

Persistent neural activity regulates Arc/Arg3.1 transcription in the dentate gyrus

The activity-regulated cytoskeleton-associated gene (Arc, also known as Arg3.1) is an effector immediate-early gene rapidly induced by strong neural activity. Although a number of studies have revealed significant functions of Arc and Arc has come into widespread use as a neural activity marker in behavioral studies, the mechanisms regulating Arc transcription remain unclear. Here, we examined the conditions of Arc transcription in acute slices of dentate gyrus. Surprisingly, kainic acid (1 μM to 10 mM) application to slices did not induce Arc transcription, although intraperitoneal injection of kainic acid (20 mg/kg) induced robust Arc transcription. No types of high-frequency stimulation examined induced Arc transcription in acute slices. These findings indicate that Arc transcription is dramatically suppressed in acute slices of the dentate gyrus, in which background neural activity is markedly reduced. Burst stimulation increased the number of Arc-expressing cells in the presence of picrotoxin, in which excitation was maintained even after the end of stimulation. Moreover, the involvement of background neural activity in Arc transcription was tested by application of carbachol, a muscarinic receptor agonist. Carbachol also increased the number of Arc-expressing cells, which was blocked by atropine, a muscarinic receptor antagonist. Taken together, these findings suggest that persistent background activity is critical for Arc transcription.

Interval timing with a beat frequency model connecting phase resetting and network response

Time perception is essential for normal physiological and behavioral responses, e.g., recalling stored data and planning future actions, and is deregulated in a series of neuropathologies, e.g., Parkinson’s disease. It is commonly accepted that processing temporal information involves a neural mechanism mimicking a stopwatch such as in the Scalar Expectancy Theory [1]. Organisms have multiple neural timing mechanisms that can span more than 10 orders of magnitude form circadian (24 hours) to interval (minutes) to millisecond timing [2]. Our focus is on modeling neural networks responsible for interval timing. In designing any computational model of interval timing, we must acknowledge an experimentally observed fact: the plot of mean response time versus the standard deviation of the distribution for different timing intervals is linear (scalar property). The established paradigm assumes an internal clock model in which pulses that are emitted regularly by a pacemaker are temporarily stored in an accumulator. At the time of reward or feedback, the number of pulses stored in the accumulator is transferred to the reference memory for future use. During “peak-interval procedure” (in which the participants are asked to reproduce the criterion interval) it is assumed that the internal clock is reset and pulses stored into accumulator until the current count match the memorized value stored during the training. The model we used assumes that timing is an emergent activity originated in the thalamo-cortico-striatal loops [2,3]. In this striatal beat-frequency (SBF) model, timing is based on the coincidental activation of medium spiny neurons in the basal ganglia by cortical neural oscillators [2,3]. The cortical oscillators are assumed to be synchronized at the onset of a trial, and to oscillate at a fixed frequency throughout the criterion interval. In our computational model, the oscillator block is composed of independent spiking neurons with intrinsic frequencies fi which, due to varying factors (biological noise, background neural activity from other cortical areas, etc.), are randomly distributed according to a certain density probability function. The synchronization of cortical oscillations at trial onset and the experience-dependent changes in cortico-striatal transmission are thought to be modulated by the dopaminergic neurons in the substatia nigra pars compacta and ventral tegmental area. A memory block stores the criterion time value c memorized during the training process. However, both storage and retrieval of criterion time to and from memory units is affected by biological context (brain state) and is modeled by randomly distributing criterion time according to a certain density probability function [3]. All timing models must connect the objective time with the subjective time. The subjective time is strongly influenced by brain’s state through neuromodulators. For example, dopamine advances the response whereas achetylcholine can induce a delay of the response in a fixed interval experiment. The mechanism involved could be through a direct change in firing frequency due to neurotransmitter action and it was modeled as a separate clock block. The decision block is an essential component of any timing mechanism that relates internal perception of time intervals with external action. A straightforward mechanism of implementing decision-making uses a set of synaptic weights derived from the memorized criterion time [3]. The weights computed from the memorized criterion constitute the reference vector of weighs. The decision block estimates the projection of the current weights on the vector of weight reference weight. The model correctly reproduced measured behavioral data.

Cortical Layer 1 and Layer 2/3 Astrocytes Exhibit Distinct Calcium Dynamics In Vivo

Cumulative evidence supports bidirectional interactions between astrocytes and neurons, suggesting glial involvement of neuronal information processing in the brain. Cytosolic calcium (Ca2+) concentration is important for astrocytes as Ca2+ surges co-occur with gliotransmission and neurotransmitter reception. Cerebral cortex is organized in layers which are characterized by distinct cytoarchitecture. We asked if astrocyte-dominant layer 1 (L1) of the somatosensory cortex was different from layer 2/3 (L2/3) in spontaneous astrocytic Ca2+ activity and if it was influenced by background neural activity. Using a two-photon laser scanning microscope, we compared spontaneous Ca2+ activity of astrocytic somata and processes in L1 and L2/3 of anesthetized mature rat somatosensory cortex. We also assessed the contribution of background neural activity to the spontaneous astrocytic Ca2+ dynamics by investigating two distinct EEG states (“synchronized” vs. “de-synchronized” states). We found that astrocytes in L1 had nearly twice higher Ca2+ activity than L2/3. Furthermore, Ca2+ fluctuations of processes within an astrocyte were independent in L1 while those in L2/3 were synchronous. Pharmacological blockades of metabotropic receptors for glutamate, ATP, and acetylcholine, as well as suppression of action potentials did not have a significant effect on the spontaneous somatic Ca2+ activity. These results suggest that spontaneous astrocytic Ca2+ surges occurred in large part intrinsically, rather than neural activity-driven. Our findings propose a new functional segregation of layer 1 and 2/3 that is defined by autonomous astrocytic activity.

Determination of Subthalamic Nucleus Location by Quantitative Analysis of Despiked Background Neural Activity From Microelectrode Recordings Obtained During Deep Brain Stimulation Surgery

Microelectrode recording during deep brain stimulation surgery is a useful adjunct for subthalamic nucleus (STN) localization. We hypothesize that information in the nonspike background activity can help identify STN boundaries. We present results from a novel quantitative analysis that accomplishes this goal. Thirteen consecutive microelectrode recordings were retrospectively analyzed. Spikes were removed from the recordings with an automated algorithm. The remaining "despiked" signals were converted via root mean square amplitude and curve length calculations into "feature profile" time series. Subthalamic nucleus boundaries determined by inspection, based on sustained deviations from baseline for each feature profile, were compared against those determined intraoperatively by the clinical neurophysiologist. Feature profile activity within STN exhibited a sustained rise in 10 of 13 tracks (77%). The sensitivity of STN entry was 60% and 90% for curve length and root mean square amplitude, respectively, when agreement within 0.5 mm of the neurophysiologist's prediction was used. Sensitivities were 70% and 100% for 1 mm accuracy. Exit point sensitivities were 80% and 90% for both features within 0.5 mm and 1.0 mm, respectively. Reproducible activity patterns in deep brain stimulation microelectrode recordings can allow accurate identification of STN boundaries. Quantitative analyses of this type may provide useful adjunctive information for electrode placement in deep brain stimulation surgery.

Baseline shifts do not predict attentional modulation of target processing during feature-based visual attention

Cues that direct selective attention to a spatial location have been observed to increase baseline neural activity in visual areas that represent a to-be-attended stimulus location. Analogous attention-related baseline shifts have also been observed in response to attention-directing cues for non-spatial stimulus features. It has been proposed that baseline shifts with preparatory attention may serve as the mechanism by which attention modulates the responses to subsequent visual targets that match the attended location or feature. Using functional MRI, we localized color- and motion-sensitive visual areas in individual subjects and investigated the relationship between cue-induced baseline shifts and the subsequent attentional modulation of task-relevant target stimuli. Although attention-directing cues often led to increased background neural activity in feature specific visual areas, these increases were not correlated with either behavior in the task or subsequent attentional modulation of the visual targets. These findings cast doubt on the hypothesis that attention-related shifts in baseline neural activity result in selective sensory processing of visual targets during feature-based selective attention.

Response dynamics of entorhinal cortex in awake, anesthetized, and bulbotomized rats

The generation of oscillatory activity may be crucial to brain function. The coordination of individual neurons into rhythmic and coherently active populations is thought to result from interactions between excitatory and inhibitory cells mediated by local feedback connections. By using extracellular recording wires and silicon microprobes to measure electrically evoked damped oscillatory responses at the level of neural populations in the entorhinal cortex, and by using current-source density analysis to determine the spatial pattern of evoked responses, we show that the propagation of activity through the cortical circuit and consequent oscillations in the local field potential are dependent upon background neural activity. Pharmacological manipulations as well as surgical disconnection of the olfactory bulb serve to quell the background excitatory input incident to entorhinal cortex, resulting in evoked responses without characteristic oscillations and showing no signs of polysynaptic feedback. Electrical stimulation at 200 Hz applied to the lateral olfactory tract provides a substitute for the normal background activity emanating from the bulb and enables the generation of oscillatory responses once again. We conclude that a non-zero background level of activity is necessary and sufficient to sustain normal oscillatory responses and polysynaptic transmission through the entorhinal cortex.