The standard pharmacological treatment for Parkinson's disease using the dopamine precursor levodopa is unfortunately limited by gradual development of disabling involuntary movements for which the underlying causes are poorly understood. Here we show that levodopa-induced dyskinesia in hemiparkinsonian rats is strongly associated with pronounced 80 Hz local field potential oscillations in the primary motor cortex following levodopa treatment. When this oscillation is interrupted by application of a dopamine antagonist onto the cortical surface the dyskinetic symptoms disappear. The finding that abnormal cortical oscillations are a key pathophysiological mechanism calls for a revision of the prevailing hypothesis that links levodopa-induced dyskinesia to an altered sensitivity to dopamine only in the striatum. Apart from having important implications for the treatment of Parkinson's disease, the discovered pathophysiological mechanism may also play a role in several other psychiatric and neurological conditions involving cortical dysfunction.

Disorders affecting the central nervous system have proven particularly hard to treat, and disappointingly few novel therapies have reached the clinics in recent decades. A better understanding of the physiological processes in the brain underlying various symptoms could therefore greatly improve the rate of progress in this field. We here show how systems-level descriptions of different brain states reliably can be obtained through a newly developed method based on large-scale recordings in distributed neural networks encompassing several different brain structures. Using this technology, we characterize the neurophysiological states associated with parkinsonism and levodopa-induced dyskinesia in a rodent model of Parkinson's disease together with pharmacological interventions aimed at reducing dyskinetic symptoms. Our results show that the obtained electrophysiological data add significant information to conventional behavioral evaluations and hereby elucidate the underlying effects of treatments in greater detail. Taken together, these results potentially open up for studies of neurophysiological mechanisms underlying symptoms in a wide range of neurological and psychiatric conditions that until now have been very hard to investigate in animal models of disease.

In the study of motor systems it is often necessary to track the movements of an experimental animal in great detail to allow for interpretation of recorded brain signals corresponding to different control signals. This task becomes increasingly difficult when analyzing complex compound movements in freely moving animals. One example of a complex motor behavior that can be studied in rodents is the skilled reaching test where animals are trained to use their forepaws to grasp small food objects, in many ways similar to human hand use. To fully exploit this model in neurophysiological research it is desirable to describe the kinematics at the level of movements around individual joints in 3D space since this permits analyses of how neuronal control signals relate to complex movement patterns. To this end, we have developed an automated system that estimates the paw pose using an anatomical paw model and recorded video images from six different image planes in rats chronically implanted with recording electrodes in neuronal circuits involved in selection and execution of forelimb movements. The kinematic description provided by the system allowed for a decomposition of reaching movements into a subset of motor components. Interestingly, firing rates of individual neurons were found to be modulated in relation to the actuation of these motor components suggesting that sets of motor primitives may constitute building blocks for the encoding of movement commands in motor circuits. The designed system will, thus, enable a more detailed analytical approach in neurophysiological studies of motor systems.

In neurophysiology, investigating brain connectivity within and between different brain structures is of fundamental importance for understanding nervous system function and its relation to behavior. Yet, parallel recordings in multiple brain structures is highly challenging, especially in rodents, which are most commonly employed in neurophysiological research but rather small in size. In this study, the design and manufacturing of a high-density multi-channel electrode for chronic, multi-structure parallel recordings in rats is presented and exemplified with functional neuronal recordings from 128 recording channels, placed bilaterally in eight different brain structures, in an awake, freely moving animal.

In natural behavior, we fluidly change from one type of activity to another in a sequence of motor actions. Corticostriatal circuits are thought to have a particularly important role in the construction of action sequences, but neuronal coding of a sequential behavior consisting of different motor programs has not been investigated at the circuit level in corticostriatal networks, making the exact nature of this involvement elusive. Here, we show, by analyzing spontaneous self-grooming in rats, that neuronal modulation in motor cortex and dorsal striatum is strongly related to transitions between behaviors. Our data suggest that longer action sequences in rodent grooming behavior emerge from stepwise control of individual behavioral transitions, where future actions are encoded differently depending on current motor state. This state-dependent motor coding was found to differentiate between rare behavioral transitions and as opposed to more habitual sequencing of actions.

The basal ganglia are thought to be particularly sensitive to changes in dopaminergic tone, and the realization that reduced dopaminergic signaling causes pronounced motor dysfunction is the rationale behind dopamine replacement therapy in Parkinson's disease. It has, however, proven difficult to identify which neurophysiological changes that ultimately lead to motor dysfunctions. To clarify this, we have here recorded neuronal activity throughout the cortico-basal ganglia-thalamic circuits in freely behaving rats during periods of immobility following acute dopaminergic manipulations, involving both vesicular dopamine depletion and antagonism of D1 and D2 type dopamine receptors. Synchronized and rhythmic activities were detected in the form of betaband oscillations in local field potentials and as cortical entrainment of action potentials in several basal ganglia structures. Analyses of the temporal development of synchronized oscillations revealed a spread from cortex to gradually also include deeper structures. In addition, firing rate changes involving neurons in all parts of the network were observed. These changes were typically relatively balanced within each structure, resulting in negligible net rate changes. Animals treated with D1 receptor antagonist showed a rapid onset of hypokinesia that preceded most of the neurophysiological changes, with the exception of these balanced rate changes. Parallel rate changes in functionally coupled ensembles of neurons in different structures may therefore be the first step in a cascade of neurophysiological changes underlying motor symptoms in the parkinsonian state. We suggest that balanced rate changes in distributed networks are possible mechanism of disease that should be further investigated in conditions involving dopaminergic dysfunction.