Temporal Spikes Research Articles

A Unique Ictal EEG Pattern in a Patient with the Coexistence of Generalized and Focal Epilepsy

The coexistence of focal and generalized epilepsy is rare. We report on a 17-year-old male with drug-resistant focal epilepsy and idiopathic generalized epilepsy (IGE). He began to experience generalized tonic-clonic seizures (GTCS) at the age of 3 years, with a good response to phenobarbital. At the age of 14 years, he began to experience complex partial seizures (CPS). Video-electroencephalography (video-EEG) telemetry showed the coexistence of right temporal spikes and bursts of generalized spike-wave (GSW). The ictal EEG showed a unique EEG pattern characterized by a 4- to 5-second burst of GSW followed by rhythmic delta activity over the right temporal region. A magnetic resonance image (MRI) showed right hippocampal sclerosis. The patient underwent a right temporal lobectomy that significantly improved his seizure control. He was rendered seizure free of the complex partial seizures and improvement of the GTCS. This case illustrates a very uncommon ictal EEG pattern, and shows that the decision for surgery in patients with focal drug-resistant epilepsy should not be affected by coexistent generalized epilepsy.

Reading spike timing without a clock: intrinsic decoding of spike trains

The precise timing of action potentials of sensory neurons relative to the time of stimulus presentation carries substantial sensory information that is lost or degraded when these responses are summed over longer time windows. However, it is unclear whether and how downstream networks can access information in precise time-varying neural responses. Here, we review approaches to test the hypothesis that the activity of neural populations provides the temporal reference frames needed to decode temporal spike patterns. These approaches are based on comparing the single-trial stimulus discriminability obtained from neural codes defined with respect to network-intrinsic reference frames to the discriminability obtained from codes defined relative to the experimenter's computer clock. Application of this formalism to auditory, visual and somatosensory data shows that information carried by millisecond-scale spike times can be decoded robustly even with little or no independent external knowledge of stimulus time. In cortex, key components of such intrinsic temporal reference frames include dedicated neural populations that signal stimulus onset with reliable and precise latencies, and low-frequency oscillations that can serve as reference for partitioning extended neuronal responses into informative spike patterns.

Theory and learning protocols for the material tempotron model

Neural networks are able to extract information from the timing of spikes. Here we provide new results on the behavior of the simplest neuronal model which is able to decode information embedded in temporal spike patterns, the so-called tempotron. Using statistical physics techniques we compute the capacity for the case of sparse, time-discretized input, and ‘material’ discrete synapses, showing that the device saturates the information theoretic bounds with a statistics of output spikes that is consistent with the statistics of the inputs. We also derive two simple and highly efficient learning algorithms which are able to learn a number of associations which are close to the theoretical limit. The simplest versions of these algorithms correspond to distributed online protocols of interest for neuromorphic devices, and can be adapted to address the more biologically relevant continuous-time version of the classification problem, hopefully allowing the understanding of some aspects of synaptic plasticity.

Reliability of MEG source imaging of anterior temporal spikes: Analysis of an intracranially characterized spike focus

ObjectiveTo assess the reliability of MEG source imaging (MSI) of anterior temporal spikes through detailed analysis of the localization and orientation of source solutions obtained for a large number of spikes that were separately confirmed by intracranial EEG to be focally generated within a single, well-characterized spike focus. MethodsMSI was performed on 64 identical right anterior temporal spikes from an anterolateral temporal neocortical spike focus. The effects of different volume conductors (sphere and realistic head model), removal of noise with low frequency filters (LFFs) and averaging multiple spikes were assessed in terms of the reliability of the source solutions. ResultsMSI of single spikes resulted in scattered dipole source solutions that showed reasonable reliability for localization at the lobar level, but only for solutions with a goodness-of-fit exceeding 80% using a LFF of 3Hz. Reliability at a finer level of intralobar localization was limited. Spike averaging significantly improved the reliability of source solutions and averaging 8 or more spikes reduced dependency on goodness-of-fit and data filtering. ConclusionsMSI performed on topographically identical individual spikes from an intracranially defined classical anterior temporal lobe spike focus was limited by low reliability (i.e., scattered source solutions) in terms of fine, sublobar localization within the ipsilateral temporal lobe. Spike averaging significantly improved reliability. SignificanceMSI performed on individual anterior temporal spikes is limited by low reliability. Reduction of background noise through spike averaging significantly improves the reliability of MSI solutions.

EEG source imaging of anterior temporal lobe spikes: Validity and reliability

ObjectiveTo assess the reliability and validity of EEG source localization of anterior temporal lobe spikes through direct comparison with simultaneously recorded intracranial spike fields. MethodsWe recently showed that classical anterior temporal spikes recorded in mesial temporal lobe epilepsy (MTLE) are non-propagated potentials generated in the anterolateral temporal neocortex (Wennberg et al., 2011). In this study EEG source imaging (ESI) was performed on 64 identical right anterior temporal spikes (and 48 homologous left anterior temporal spikes) in a patient with MTLE investigated with simultaneous depth and subdural intracranial EEG and 27 channel scalp EEG. The effects of different realistic forward models, low frequency filters (LFFs) and spike averaging were assessed in terms of the reliability and physiologic validity of the source solutions. ResultsDipole mapping and distributed source modeling solutions for the grand average of all spikes were accurately localized to the superficial anterolateral temporal neocortex within 1cm of the intracranially defined spike generator, irrespective of forward model or LFF. ESI of single spikes, however, showed poor reliability (i.e., dissimilar localization results for intracranially identical spikes). Even with an optimal combination of individualized volume conductor and 3Hz LFF more than one third of single spike source solutions were physiologically invalid. Spike averaging, especially of 8 or more spikes, significantly increased the proportion of valid source solutions. ConclusionsESI of individual anterior temporal spikes was limited by low reliability and a high likelihood of physiologically invalid source solutions. Spike averaging of 8 or more identical spikes prior to ESI, however, reliably produced accurate source solutions localized to the anterolateral temporal neocortex. SignificanceESI performed on averages of identical spikes can provide highly accurate noninvasive source localization of the anterolateral temporal neocortical region responsible for generating classical anterior temporal lobe spikes. The reliability and validity of ESI performed on individual spikes, however, is relatively limited.

Postnatal development of temporal integration, spike timing and spike threshold regulation by a dendrotoxin‐sensitive K+ current in rat CA1 hippocampal cells

Spike timing and network synchronization are important for plasticity, development and maturation of brain circuits. Spike delays and timing can be strongly modulated by a low-threshold, slowly inactivating, voltage-gated potassium current called D-current (ID ). ID can delay the onset of spiking, cause temporal integration of multiple inputs, and regulate spike threshold and network synchrony. Recent data indicate that ID can also undergo activity-dependent, homeostatic regulation. Therefore, we have studied the postnatal development of ID -dependent mechanisms in CA1 pyramidal cells in hippocampal slices from young rats (P7-27), using somatic whole-cell recordings. At P21-27, these neurons showed long spike delays and pronounced temporal integration in response to a series of brief depolarizing current pulses or a single long pulse, whereas younger cells (P7-20) showed shorter discharge delays and weak temporal integration, although the spike threshold became increasingly negative with maturation. Application of α-dendrotoxin (α-DTX), which blocks ID , reduced the spiking latency and temporal integration most strongly in mature cells, while shifting the spike threshold most strongly in a depolarizing direction in these cells. Voltage-clamp analysis revealed an α-DTX-sensitive outward current (ID ) that increased in amplitude during development. In contrast to P21-23, ID in the youngest group (P7-9) showed smaller peri-threshold amplitude. This may explain why long discharge delays and robust temporal integration only appear later, 3 weeks postnatally. We conclude that ID properties and ID -dependent functions develop postnatally in rat CA1 pyramidal cells, and ID may modulate network activity and plasticity through its effects on synaptic integration, spike threshold, timing and synchrony.

22. Seizure-induced ictal asystolia: A serious complication of seizures revealed by long-term video-EEG monitoring

Sudden unexpected death in epilepsy (SUDEP) represents the main cause of death in patients with refractory epilepsy. A number of mechanisms have been proposed, including seizure-induced asystolia. We report two new patients with ictal asystolia revealed by long-term video-EEG monitoring. Case 1. A 76 year-old male with 1 year history of sudden falls to the ground associated with loss of consciousness, pallor and sweating, sometimes preceded by an olfactory hallucination. EEG: left temporal spikes. MRI: cerebral vascular changes. Case 2. A 55 year-old male with a 10 year history of focal seizures characterized by epigastric aura and loss of contact, more recently followed by sudden falls to the ground with pallor and stiffening. EEG: left temporal spikes. MRI: left temporal dysplasia. The video-EEG monitoring allowed to capture a number of seizures originating from the left temporal lobe and associated with ictal asystolia lasting for 10–20 s, with a corresponding syncope-like EEG picture. Focal seizures complicated by ictal asystolia may be suspected on clinical grounds by the appearance of syncope-like events preceded by typical epileptic auras. Long-term video-EEG recording is the gold standard to detect these events which may require pacemaker implantation.

Epilepsy and electroencephalographic features in trisomy 13: A case report and review of literature

Epilepsy and electroencephalographic features in trisomy 13: A case report and review of literature

Role of synaptic dynamics and heterogeneity in neuronal learning of temporal code

Temporal codes are believed to play important roles in neuronal representation of information. Neuronal ability to classify and learn temporal spiking patterns is thus essential for successful extraction and processing of information. Understanding neuronal learning of temporal code has been complicated, however, by the intrinsic stochasticity of synaptic transmission. Using a computational model of a learning neuron, the tempotron, we studied the effects of synaptic unreliability and short-term dynamics on the neuron's ability to learn spike timing rules. Our results suggest that such a model neuron can learn to classify spike timing patterns even with unreliable synapses, albeit with a significantly reduced success rate. We explored strategies to improve correct spike timing classification and found that firing clustered spike bursts significantly improves learning performance. Furthermore, rapid activity-dependent modulation of synaptic unreliability, implemented with realistic models of dynamic synapses, further improved classification of different burst properties and spike timing modalities. Neuronal models with only facilitating or only depressing inputs exhibited preference for specific types of spike timing rules, but a mixture of facilitating and depressing synapses permitted much improved learning of multiple rules. We tested applicability of these findings to real neurons by considering neuronal learning models with the naturally distributed input release probabilities found in excitatory hippocampal synapses. Our results suggest that spike bursts comprise several encoding modalities that can be learned effectively with stochastic dynamic synapses, and that distributed release probabilities significantly improve learning performance. Synaptic unreliability and dynamics may thus play important roles in the neuron's ability to learn spike timing rules during decoding.

S17-4. Dense array EEG – Clinical application in epilepsy

The purpose of this study is to evaluate the clinical usefulness of dense array EEG (dEEG) for spike detection yield (sensitivity) and localization (accuracy) of interictal spikes in temporal lobe epilepsy. The subjects were 6 patients who had implanted subdural electrodes in both mesial and lateral temporal regions for presurgical work-up. Simultaneous dEEG and intracranial EEG (icEEG) were recorded. We calculated dEEG spike detection rate and applied spike source estimation for mesial temporal spikes. 45% of the spikes were detected by dEEG with 256ch head surface array. The average icEEG amplitude of dEEG detectable spikes was 1236 μ V, and that of dEEG undetectable spikes was 894rmuV ( P

Modulation of a decision-making process by spatiotemporal spike patterns decoding: evidence from spike-train metrics analysis and spiking neural network modeling

While monkeys perform a task alternating between behavioral adaptation --relying on feedback monitoring and memory of previous choices-- and repetition of previous actions, firing rates in dorsal Anterior Cingulate Cortex (dACC) modulate with cognitive control levels [1]. Further, it has been hypothesized that dorsolateral Prefrontal Cortex (dlPFC) could make use of dACC signals to take the adapted decision [2]. However, little is known about whether dACC spike timing may participate to behavioral adaptation signaling, and how multiple unit activities may be jointly decoded by dlPFC. We tested the hypothesis that temporal (or spatiotemporal) pattern matching mediate information transmission by dACC. We used spike-train metrics [3] to decode dACC activity recorded in a problem solving task [1] (336 cells, 2 monkeys). We computed a similarity measure between every spike train and the activity patterns in different task epochs for classification. When computing the similarity, we explored different degrees of (i) timing sensitivity and (ii) distinction between spikes from different neurons, which led to different classification performances. We found that timing sensitivity could improve behavioral adaptation vs. repetition classification of single unit spike trains. Optimal decoding occurred when accounting for spike times at a resolution <= 200 ms. Furthermore, spike-train metrics decoding of unitary discharges was related to the monkeys' response time. A downstream neural decoder could exploit this temporal information through coincidence detection determined by synaptic and membrane time constants. In addition, when decoding two units jointly, we found that each pair had a specific optimal distinction degree between spikes coming from the two different neurons. In a realistic neural decoder, the tuning of this distinction degree might occur through non-linear dendritic integration. To further investigate the computational properties of temporal decoding in the context of decision-making, we are implementing a recurrent spiking neural network with connectivity leading to attractor dynamics. In this framework, each decision is mapped to a state in which a corresponding neural subpopulation shows elevated activity, as observed experimentally in dlPFC [4]. In addition, neurons will undergo membrane properties adaptation [5] and short-term plasticity, leading to history-of-choices dependent temporal spike patterns. We will investigate how this temporal-spike-patterns memory of past choices could interact with dACC feedback-specific temporal patterns to lead to adapted decision. The feasibility and putative advantages of spike-timing-dependent-plasticity-based learning of response selectivity to the appropriate dACC-dlPFC temporal correlations will be considered.

Temporal Lobe Epilepsy With Hippocampal Sclerosis in Acute Lymphoblastic Leukemia

Of 71 acute lymphoblastic leukemia survivors at our hospital over the past 10 years, 2 children developed mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS). This is the first report to describe the clinical course of MTLE-HS observed longitudinally by EEG and MRI. Patient 1 experienced a seizure during chemotherapy involving intrathecal methotrexate. Postseizure MRI suggested methotrexate encephalopathy or leukemic invasion. Anticonvulsant therapy was initiated; subsequent EEGs and MRIs revealed normal results. Three years after chemotherapy, a diffuse, irregular spike-and-wave pattern was observed on interictal EEG. Five years after chemotherapy, the patient developed MTLE-HS comprising complex partial seizures, typical temporal spikes on EEG, and hippocampal sclerosis (HS). Patient 2 did not experience seizures during chemotherapy. Four years later, the patient started experiencing complex partial seizures, and a diffuse, irregular spike-and-wave pattern was observed on interictal EEG. A clinical picture of MTLE-HS developed 2 years later. In both patients, nonspecific EEG abnormalities (ie, diffuse, irregular spike-and-wave activity) preceded the appearance of HS on MRI by 2 years, suggesting an insidious advance of HS during the latent period. Such atypical EEG findings may indicate MTLE-HS during follow-up of leukemia patients. MTLE-HS develops several years after an initial precipitating incident such as prolonged seizures, central nervous system infection, and brain trauma. In our cases, the initial precipitating incident may have been chemotherapy and/or prolonged seizures. Thus, MTLE-HS associated with leukemia may not be as rare as generally believed. A large cohort study of late neurologic complications is warranted.

Cortical Inhibition Reduces Information Redundancy at Presentation of Communication Sounds in the Primary Auditory Cortex

In all sensory modalities, intracortical inhibition shapes the functional properties of cortical neurons but also influences the responses to natural stimuli. Studies performed in various species have revealed that auditory cortex neurons respond to conspecific vocalizations by temporal spike patterns displaying a high trial-to-trial reliability, which might result from precise timing between excitation and inhibition. Studying the guinea pig auditory cortex, we show that partial blockage of GABAA receptors by gabazine (GBZ) application (10 μm, a concentration that promotes expansion of cortical receptive fields) increased the evoked firing rate and the spike-timing reliability during presentation of communication sounds (conspecific and heterospecific vocalizations), whereas GABAB receptor antagonists [10 μm saclofen; 10-50 μm CGP55845 (p-3-aminopropyl-p-diethoxymethyl phosphoric acid)] had nonsignificant effects. Computing mutual information (MI) from the responses to vocalizations using either the evoked firing rate or the temporal spike patterns revealed that GBZ application increased the MI derived from the activity of single cortical site but did not change the MI derived from population activity. In addition, quantification of information redundancy showed that GBZ significantly increased redundancy at the population level. This result suggests that a potential role of intracortical inhibition is to reduce information redundancy during the processing of natural stimuli.

Spike-Based Probabilistic Inference in Analog Graphical Models Using Interspike-Interval Coding

Temporal spike codes play a crucial role in neural information processing. In particular, there is strong experimental evidence that interspike intervals (ISIs) are used for stimulus representation in neural systems. However, very few algorithmic principles exploit the benefits of such temporal codes for probabilistic inference of stimuli or decisions. Here, we describe and rigorously prove the functional properties of a spike-based processor that uses ISI distributions to perform probabilistic inference. The abstract processor architecture serves as a building block for more concrete, neural implementations of the belief-propagation (BP) algorithm in arbitrary graphical models (e.g., Bayesian networks and factor graphs). The distributed nature of graphical models matches well with the architectural and functional constraints imposed by biology. In our model, ISI distributions represent the BP messages exchanged between factor nodes, leading to the interpretation of a single spike as a random sample that follows such a distribution. We verify the abstract processor model by numerical simulation in full graphs, and demonstrate that it can be applied even in the presence of analog variables. As a particular example, we also show results of a concrete, neural implementation of the processor, although in principle our approach is more flexible and allows different neurobiological interpretations. Furthermore, electrophysiological data from area LIP during behavioral experiments are assessed in light of ISI coding, leading to concrete testable, quantitative predictions and a more accurate description of these data compared to hitherto existing models.

Spike bursts increase amyloid-β 40/42 ratio by inducing a presenilin-1 conformational change

Accumulated genetic evidence suggests that attenuation of the ratio between cerebral amyloid-β Aβ40 and Aβ42 isoforms is central to familial Alzheimer's disease (FAD) pathogenesis. However, FAD mutations account for only 1-2% of Alzheimer's disease cases, leaving the experience-dependent mechanisms regulating Aβ40/42 an enigma. Here we explored regulation of Aβ40/42 ratio by temporal spiking patterns in the rodent hippocampus. Spike bursts boosted Aβ40/42 through a conformational change in presenilin1 (PS1), the catalytic subunit of γ-secretase, and subsequent increase in Aβ40 production. Conversely, single spikes did not alter basal PS1 conformation and Aβ40/42. Burst-induced PS1 conformational shift was mediated by means of Ca(2+)-dependent synaptic vesicle exocytosis. Presynaptic inhibition in vitro and visual deprivation in vivo augmented synaptic and Aβ40/42 facilitation by bursts in the hippocampus. Thus, burst probability and transfer properties of synapses represent fundamental features regulating Aβ40/42 by experience and may contribute to the initiation of the common, sporadic Alzheimer's disease.

MELAS syndrome diagnosed in ICU in a 56-year-old patient presenting with status epilepticus

The differential diagnosis of stroke in a middle-aged adult usually does not include the mitochondrial myopathy, encephalopathy, lactic acidosis and strokelike episodes syndrome (MELAS), because such a manifestation very rarely first occurs after the age of 40 [1, 2]. We report the case of a 56-year-old woman, brought to our hospital with irritability, aphasia, and ataxic gait. A brain computed tomography revealed a hypodense area on the left temporal lobe (Fig. 1). Ten hours later she developed convulsive status epilepticus and loss of consciousness. She was treated with phenytoin and transferred to the ICU, mechanically ventilated and sedated with propofol. Her past medical history was marked for a hearing deficit, for which a cochlear implant had been inserted 2 years earlier, and for an episode of loss of consciousness 6 months earlier. She was functional with daily activities. The patient was childless. Three out of her four sisters had died at early age. On ICU admission, physical examination revealed right hemiparesis. Pupils were equal and reactive and vital signs were within normal range. Fundoscopic examination was normal. Laboratory parameters were unremarkable, with the exception of white-cell count 18,900/mm (85 % neutrophils), aspartate aminotransferase 274 U/L, alanine aminotransferase 82 U/L, creatine kinase 9,705 U/L and lactate 3.3 mmol/L. Cerebrospinal fluid (CSF) examination was normal. The electroencephalogram showed frequent temporal spikes and slow wave complexes. Extensive imaging for brain vascular disease and laboratory investigation for autoimmune or infectious brain disease all proved negative. Magnetic resonance imaging was avoided due to the presence of the cochlear implant. On ICU day 7, the patient remained comatose. Persistent elevated blood lactate (2.5–5.3 mmol/L) was noted, despite clinical absence of seizures or haemodynamic instability. Repeat CSF revealed lactate 4.3 mmol/ L, not measured in the first sample. A mitochondrial encephalopathy was then suspected. A quadriceps muscle biopsy specimen revealed ‘‘ragged red fibres’’, corroborating the diagnosis of MELAS. Relatives declined further investigation with mitochondrial DNA analysis because the result would not affect the patient’s management, and there was no reason for genetic counseling. The patient had a slow neurological improvement; she weaned from mechanical ventilation and 44 days after ICU admission she was transferred to a rehabilitation center with a Glasgow Coma Scale of 13. First described in 1984, MELAS is a rare, maternally inherited clinical entity resulting from mutations in the mitochondrial DNA [1, 2]. The term ‘‘strokelike’’ refers to clinical and radiological impression of brain ischemia, albeit not conformed to a vascular territory. Although their pathogenesis remains unclear, relative deficiency of cellular adenosine triphoshate has been implicated [3]. According to diagnostic criteria, ‘‘strokelike’’ episodes have to appear before the age of 40 [2]. Few cases occur after the age of 50 [2–5] and none was first diagnosed in the ICU setting. Partial and complex partial status epilepticus are more commonly seen than generalized convulsive status epilepticus in MELAS [6]. ICU

An energy-efficient spike encoding circuit for speech edge detection

In speech processing applications, the instantaneous bandwidth of speech can be used to adaptively control the performance of an audio sensor's analog front end. Extracting the instantaneous bandwidth of speech depends on the detection of speech edges in the time---frequency plane. In this paper, we propose a spike encoding circuit for real-time and low-power speech edge detection. The circuit can directly encode the signal's envelope information--an important feature to identify the speech edge--by temporal spike density without additional envelope extraction. Furthermore, the spike encoding circuit automatically adapts its resolution to the amplitude of the input signal, which improves the encoding resolution for small signal without increasing the power consumption. We use the nonlinear dynamical approach to design this circuit and analyze its stability. We also develop a linearized model for this circuit to provide the design intuition and to explain its adaptive resolution. Fabricated in 0.5-μm CMOS process, the spike encoding circuit consumes 0.3-μW power and the experimental results are presented.

Computing Complex Visual Features with Retinal Spike Times

Neurons in sensory systems can represent information not only by their firing rate, but also by the precise timing of individual spikes. For example, certain retinal ganglion cells, first identified in the salamander, encode the spatial structure of a new image by their first-spike latencies. Here we explore how this temporal code can be used by downstream neural circuits for computing complex features of the image that are not available from the signals of individual ganglion cells. To this end, we feed the experimentally observed spike trains from a population of retinal ganglion cells to an integrate-and-fire model of post-synaptic integration. The synaptic weights of this integration are tuned according to the recently introduced tempotron learning rule. We find that this model neuron can perform complex visual detection tasks in a single synaptic stage that would require multiple stages for neurons operating instead on neural spike counts. Furthermore, the model computes rapidly, using only a single spike per afferent, and can signal its decision in turn by just a single spike. Extending these analyses to large ensembles of simulated retinal signals, we show that the model can detect the orientation of a visual pattern independent of its phase, an operation thought to be one of the primitives in early visual processing. We analyze how these computations work and compare the performance of this model to other schemes for reading out spike-timing information. These results demonstrate that the retina formats spatial information into temporal spike sequences in a way that favors computation in the time domain. Moreover, complex image analysis can be achieved already by a simple integrate-and-fire model neuron, emphasizing the power and plausibility of rapid neural computing with spike times.

Akinetopsia as epileptic seizure.

Akinetopsia is a rare syndrome in which a patient specifically loses the ability to perceive visual motion following bilateral cortical lesions outside the striate cortex. We describe a patient who showed akinetopsia recurrently as epileptic seizures.The patient was a 61-year-old man. At age 46, a cerebral arteriovenous malformation in the right parietal lobe was discovered. At age 58, he began to have a recurrent visual symptom by which smooth movements of objects suddenly appeared, resembling freeze frames in a motion picture. This symptom was paroxysmal and recurrent. Both EEG and magnetoencephalography showed repetitive right temporal spikes. We diagnosed his visual symptom as akinetopsia, which was aroused by hyperexcitability of the right temporal and parietal cortices, including area MT/V5. We administered carbamazepine 200 mg/day, which suppressed his akinetopsic symptom completely.

Inducing Gamma Oscillations and Precise Spike Synchrony by Operant Conditioning via Brain-Machine Interface

Neural oscillations in the low-gamma range (30-50 Hz) have been implicated in neuronal synchrony, computation, behavior, and cognition. Abnormal low-gamma activity, hypothesized to reflect impaired synchronization, has been evidenced in several brain disorders. Thus, understanding the relations between gamma oscillations, neuronal synchrony and behavior is a major research challenge. We used a brain-machine interface (BMI) to train monkeys to specifically increase low-gamma power in selected sites of motor cortex to move a cursor and obtain a reward. The monkeys learned to robustly generate oscillatory gamma waves, which were accompanied by a dramatic increase of spiking synchrony of highly precise spatiotemporal patterns. The findings link volitional control of LFP oscillations, neuronal synchrony, and the behavioral outcome. Subjects' ability to directly modulate specific patterns of neuronal synchrony provides a powerful approach for understanding neuronal processing in relation to behavior and for the use of BMIs in a clinical setting.