Ole Jensen

Frontal theta activity in humans increases with memory load in a working memory task

Recent theoretical work has suggested that brain oscillations in the theta band are involved in active maintenance and recall of working memory representations. To test this theoretical framework we recorded neuromagnetic responses from 10 subjects performing the Sternberg task. Subjects were required to retain a list of 1, 3, 5 or 7 visually presented digits during a 3‐s retention period. During the retention period we observed ongoing frontal theta activity in the 7–8.5‐Hz band recorded by sensors over frontal brain areas. The activity in the theta band increased parametrically with the number of items retained in working memory. A time–frequency analysis revealed that the task‐dependent theta was present during the retention period and during memory scanning. Following the memory task the theta activity was reduced. These results suggest that theta oscillations generated in frontal brain regions play an active role in memory maintenance.

On the human sensorimotor-cortex beta rhythm: sources and modeling.

Cortical oscillations in the beta band (13-35 Hz) are known to be modulated by the GABAergic agonist benzodiazepine. To investigate the mechanisms generating the approximately 20-Hz oscillations in the human cortex, we administered benzodiazepines to healthy adults and monitored cortical oscillatory activity by means of magnetoencephalography. Benzodiazepine increased the power and decreased the frequency of beta oscillations over rolandic areas. Minimum current estimates indicated the effect to take place around the hand area of the primary sensorimotor cortex. Given that previous research has identified sources of the beta rhythm in the motor cortex, our results suggest that these same motor-cortex beta sources are modulated by benzodiazepine. To explore the mechanisms underlying the increase in beta power with GABAergic inhibition, we simulated a conductance-based neuronal network comprising excitatory and inhibitory neurons. The model accounts for the increase in the beta power, the widening of the spectral peak, and the slowing down of the rhythms with benzodiazepines, implemented as an increase in GABAergic conductance. We found that an increase in IPSCs onto inhibitory neurons was more important for generating neuronal synchronization in the beta band than an increase in IPSCs onto excitatory pyramidal cells.

Neuromagnetic localization of rhythmic activity in the human brain: A comparison of three methods

Cortical rhythmic activity is increasingly employed for characterizing human brain function. Using MEG, it is possible to localize the generators of these rhythms. Traditionally, the source locations have been estimated using sequential dipole modeling. Recently, two new methods for localizing rhythmic activity have been developed, Dynamic Imaging of Coherent Sources (DICS) and Frequency-Domain Minimum Current Estimation (MCE(FD)). With new analysis methods emerging, the researcher faces the problem of choosing an appropriate strategy. The aim of this study was to compare the performance and reliability of these three methods. The evaluation was performed using measured data from four healthy subjects, as well as with simulations of rhythmic activity. We found that the methods gave comparable results, and that all three approaches localized the principal sources of oscillatory activity very well. Dipole modeling is a very powerful tool once appropriate subsets of sensors have been selected. MCE(FD) provides simultaneous localization of sources and was found to give a good overview of the data. With DICS, it was possible to separate close-by sources that were not retrieved by the other two methods.

A New Method to Identify Multiple Sources of Oscillatory Activity from Magnetoencephalographic Data

Identifying the sources of oscillatory activity in the human brain is a challenging problem in current magnetoencephalography (MEG) and electroencephalography (EEG) research. The fluctuations in phase and amplitude of cortical oscillations preclude signal averaging over successive sections of the data without a priori assumptions. In addition, several sources at different locations often produce oscillatory activity at similar frequencies. For example, spontaneous oscillatory activity in the 8- to 13-Hz band is produced simultaneously at least in the posterior parts of the brain and bilaterally in the sensorimotor cortices. The previous approaches of identifying sources of oscillatory activity by dipole modeling of bandpass filtered data are quite laborious and require that multiple criteria are defined by an experienced user. In this work we introduce a convenient method for source localization using minimum current estimates in the frequency domain. Individual current estimates are calculated for the Fourier transforms of successive sections of continuous data. These current estimates are then averaged. The algorithm was tested on simulated and measured MEG data and compared with conventional dipole modeling. The main advantage of the proposed method is that it provides an efficient approach for simultaneous estimation of multiple sources of oscillatory activity in the same frequency band.

Information Transfer Between Rhythmically Coupled Networks: Reading the Hippocampal Phase Code

There are numerous reports on rhythmic coupling between separate brain networks. It has been proposed that this rhythmic coupling indicates exchange of information. So far, few computational models have been proposed that explore this principle and its potential computational benefits. Recent results on hippocampal place cells of the rat provide new insight; it has been shown that information about space is encoded by the firing of place cells with respect to the phase of the ongoing theta rhythm. This principle is termed phase coding and suggests that upcoming locations (predicted by the hippocampus) are encoded by cells firing late in the theta cycle, whereas current location is encoded by early firing in the theta cycle. A network reading the hippocampal output must inevitably also receive an oscillatory theta input in order to decipher the phase-coded firing patterns. In this article, I propose a simple physiologically plausible mechanism implemented as an oscillatory network that can decode the hippocampal output. By changing only the phase of the theta input to the decoder, qualitatively different information is transferred: the theta phase determines whether representations of current or upcoming locations are read by the decoder. The proposed mechanism provides a computational principle for information transfer between oscillatory networks and might generalize to brain networks beyond the hippocampal region.

Abnormal Reactivity of the ;20-Hz Motor Cortex Rhythm in Unverricht Lundborg Type Progressive Myoclonus Epilepsy

Abstract The ∼20-Hz component of the human mu rhythm originates predominantly in the primary motor cortex. We monitored with a whole-scalp neuromagnetometer the reactivity of the ∼20-Hz rhythm as an index of the functional state of the primary motor cortex in seven patients suffering from Unverricht–Lundborg type (ULD) progressive myoclonus epilepsy (PME) and in seven healthy control subjects. In patients, the motor cortex rhythm was on average 5 Hz lower in frequency and its strength was double compared with controls. To study reactivity of the ∼20-Hz rhythm, left and right median nerves were stimulated alternately at wrists. In controls, these stimuli elicited a small transient decrease, followed by a strong increase (“rebound”) of the ∼20-Hz level. In contrast, the patients showed no significant rebounds of the rhythm. As the ∼20-Hz rebounds apparently reflect increased cortical inhibition, our results indicate that peripheral stimuli excite motor cortex for prolonged periods in patients with ULD.

Visually Evoked Gamma Responses in the Human Brain Are Enhanced during Voluntary Hyperventilation

Hypocapnia induced by hyperventilation (HV) has powerful effects on neuronal excitability and synaptic transmission. We have studied the effect of hyperventilation on the phase-locked oscillatory components of the evoked responses in the human brain. We recorded visually evoked magnetoencephalographic responses before, during, and after voluntary hyperventilation to pattern-reversal checkerboard stimuli. Gamma-band (30-45 Hz) responses phase-locked to the stimuli were generated in the occipital visual cortex. A wavelet-based time-frequency analysis revealed that the gamma responses increased during HV whereas their frequency did not change significantly. A recent in vitro study in the rat hippocampus demonstrated that the stability of spontaneous gamma activity increases during hypocapnia as a result of enhanced GABAergic transmission. To test if a similar mechanism could account for our findings, we performed simulations on a network of 100 Hodgkin-Huxley neurons connected by inhibitory synapses. We found that enhanced GABA(A) transmission, paired with enhanced excitability, can explain the increase in evoked gamma activity without changing the frequency.

Dual oscillations as the physiological basis for capacity limits

A physiological model for short-term memory (STM) based on dual theta (5–10 Hz) and gamma (20–60 Hz) oscillation was proposed by Lisman and Idiart (1995). In this model a memory is represented by groups of neurons that fire in the same gamma cycle. According to this model, capacity is determined by the number of gamma cycles that occur within the slower theta cycle. We will discuss here the implications of recent reports on theta oscillations recorded in humans performing the Sternberg task. Assuming that the oscillatory memory models are correct, these findings can help determine STM capacity.