Summary Neuronal oscillations allow for temporal segmentation of neuronal spikes. Interdependent oscillators can integrate multiple layers of information. We examined phase-phase coupling of theta and gamma oscillators in the CA1 region of rat hippocampus during maze exploration and REM sleep. Hippocampal theta waves were asymmetric, and estimation of the spatial position of the animal was improved by identifying the waveform-based phase of spiking, compared to traditional methods used for phase estimation. Using the waveform-based theta phase, 3 distinct gamma bands were identified: slow gammaS (30-50 Hz), mid-frequency gammaM (50-90 Hz) and fast gammaF (90-150 Hz or epsilon band). The amplitude of each sub-band was modulated by the theta phase. In addition, we found reliable phase-phase coupling between theta and both gammaS and gammaM but not gammaF oscillators. We suggest that cross-frequency phase coupling can support multiple time-scale control of neuronal spikes within and across structures.

Developments in microfabrication technology have enabled the production of neural electrode arrays with hundreds of closely-spaced recording sites, and electrodes with thousands of sites are currently under development. These probes in principle allow the simultaneous recording of very large numbers of neurons. However, use of this technology requires the development of techniques for decoding the spike times of the recorded neurons, from the raw data captured from the probes. Here, we present a set of novel tools to solve this problem, implemented in a suite of practical, user-friendly, open-source software. We validate these methods on data from the cortex, hippocampus, and thalamus of rat, mouse, macaque, and marmoset, demonstrating error rates as low as 5%.

Low intensity electric fields have been suggested to affect the ongoing neuronal activity in vitro and in human studies. However, the physiological mechanism of how weak electrical fields affect and interact with intact brain activity is not well understood. We performed in vivo extracellular and intracellular recordings from the neocortex and hippocampus of anesthetized rats and extracellular recordings in behaving rats. Electric fields were generated by sinusoid patterns at slow frequency (0.8, 1.25 or 1.7 Hz) via electrodes placed on the surface of the skull or the dura. Transcranial electric stimulation (TES) reliably entrained neurons in widespread cortical areas, including the hippocampus. The percentage of TES phase-locked neurons increased with stimulus intensity and depended on the behavioral state of the animal. TES-induced voltage gradient, as low as 1 mV/mm at the recording sites, was sufficient to phase-bias neuronal spiking. Intracellular recordings showed that both spiking and subthreshold activity were under the combined influence of TES forced fields and network activity. We suggest that TES in chronic preparations may be used for experimental and therapeutic control of brain activity.

Many neurological and psychiatric diseases are associated with clinically detectable, altered brain dynamics. The aberrant brain activity, in principle, can be restored through electrical stimulation. In epilepsies, abnormal patterns emerge intermittently, and therefore, a closed-loop feedback brain control that leaves other aspects of brain functions unaffected is desirable. Here, we demonstrate that seizure-triggered, feedback transcranial electrical stimulation (TES) can dramatically reduce spike-and-wave episodes in a rodent model of generalized epilepsy. Closed-loop TES can be an effective clinical tool to reduce pathological brain patterns in drug-resistant patients.

A major challenge in neuroscience is linking behavior to the collective activity of neural assemblies. Understanding of input-output relationships of neurons and circuits requires methods with the spatial selectivity and temporal resolution appropriate for mechanistic analysis of neural ensembles in the behaving animal, i.e. recording of representatively large samples of isolated single neurons. Ensemble monitoring of neuronal activity has progressed remarkably in the past decade in both small and large-brained animals, including human subjects 1-11 . Multiple-site recording with silicon-based devices are particularly effective because of their scalability, small volume and geometric design.

A high proportion of neurons in the basal ganglia display rhythmic burst firing after chronic nigrostriatal lesions. For instance, the periodic bursts exhibited by certain striatal and subthalamic nucleus neurons in 6-hydroxydopamine-lesioned rats seem to be driven by the approximately 1 Hz high-amplitude rhythm that is prevalent in the cerebral cortex of anaesthetized animals. Because the striatum and subthalamic nucleus are the main afferent structures of the substantia nigra pars reticulata, we examined the possibility that the low-frequency modulations (periodic bursts) that are evident in approximately 50% nigral pars reticulata neurons in the parkinsonian condition were also coupled to this slow cortical rhythm. By recording the frontal cortex field potential simultaneously with single-unit activity in the substantia nigra pars reticulata of anaesthetized rats, we proved the following. (i) The firing of nigral pars reticulata units from sham-lesioned rats is not coupled to the approximately 1 Hz frontal cortex slow oscillation. (ii) Approximately 50% nigral pars reticulata units from 6-hydroxydopamine-lesioned rats oscillate synchronously with the approximately 1 Hz cortical rhythm, with the cortex leading the substantia nigra by approximately 55 ms; the remaining approximately 50% nigral pars reticulata units behave as the units recorded from sham-lesioned rats. (iii) Periodic bursting in nigral pars reticulata units from 6-hydroxydopamine-lesioned rats is disrupted by episodes of desynchronization of cortical field potential activity. Our results strongly support that nigrostriatal lesions promote the spreading of low-frequency cortical rhythms to the substantia nigra pars reticulata and may be of outstanding relevance for understanding the pathophysiology of Parkinson's disease.

Motor execution and planning are tightly regulated by dopamine D1 and D2 receptors present in basal ganglia circuits. Although stimulation of D1 receptors is known to enhance motor function, the global effect of D2 receptor (D2R) stimulation or blockade remains highly controversial, with studies showing increasing, decreasing or no changes in motor activity. Moreover, pharmacological and genetic attempts to block or eliminate D2R have led to controversial results that questioned the importance of D2R in motor function. In this study, we generated an inducible Drd2 null-allele mouse strain that circumvented developmental compensations found in constitutive Drd2 mice and allowed us to directly evaluate the participation of D2R in spontaneous locomotor activity and motor learning. We have found that loss of D2R during adulthood causes severe motor impairments, including hypolocomotion, deficits in motor coordination, impaired learning of new motor routines and spontaneous catatonia. Moreover, severe motor impairment, resting tremor and abnormal gait and posture, phenotypes reminiscent of Parkinson's disease, were evident when the mutation was induced in aged mice. Altogether, the conditional Drd2 knockout model studied here revealed the overall fundamental contribution of D2R in motor functions and explains some of the side effects elicited by D2R blockers when used in neurological and psychiatric conditions, including schizophrenia, bipolar disorder, Tourette's syndrome, dementia, alcohol-induced delusions and obsessive-compulsive disorder.

Developments in microfabrication technology have enabled the production of neural electrode arrays with hundreds of closely-spaced recording sites, and electrodes with thousands of sites are currently under development. These probes in principle allow the simultaneous recording of very large numbers of neurons. However, use of this technology requires the development of techniques for decoding the spike times of the recorded neurons, from the raw data captured from the probes. Here, we present a set of novel tools to solve this problem, implemented in a suite of practical, user-friendly, open-source software. We validate these methods on data from the cortex, hippocampus, and thalamus of rat, mouse, macaque, and marmoset, demonstrating error rates as low as 5%.Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use