Retuning of Inferior Colliculus Neurons Following Spiral Ganglion Lesions: A Single-Neuron Model of Converging Inputs

Lesions of spiral ganglion cells, representing a restricted sector of the auditory nerve array, produce immediate changes in the frequency tuning of inferior colliculus (IC) neurons. There is a loss of excitation at the lesion frequencies, yet responses to adjacent frequencies remain intact and new regions of activity appear. This leads to immediate changes in tuning and in tonotopic progression. Similar effects are seen after different methods of peripheral damage and in auditory neurons in other nuclei. The mechanisms that underlie these postlesion changes are unknown, but the acute effects seen in IC strongly suggest the “unmasking” of latent inputs by the removal of inhibition. In this study, we explore computational models of single neurons with a convergence of excitatory and inhibitory inputs from a range of characteristic frequencies (CFs), which can simulate the narrow prelesion tuning of IC neurons, and account for the changes in CF tuning after a lesion. The models can reproduce the data if inputs are aligned relative to one another in a precise order along the dendrites of model IC neurons. Frequency tuning in these neurons approximates that seen physiologically. Removal of inputs representing a narrow range of frequencies leads to unmasking of previously subthreshold excitatory inputs, which causes changes in CF. Conversely, if all of the inputs converge at the same point on the cell body, receptive fields are broad and unmasking rarely results in CF changes. However, if the inhibition is tonic with no stimulus-driven component, then unmasking can still produce changes in CF

Searching for the elusive typhoid diagnostic

Typhoid (enteric) fever is still a common disease in many developing countries but current diagnostic tests are inadequate. Studies on pathogenesis and genomics have provided new insight into the organisms that cause enteric fever. Better understanding of the microorganisms explains, in part, why our current typhoid methodologies are limited in their diagnostic information and why developing new strategies may be a considerable challenge. Here we discuss the current position of typhoid diagnostics, highlight the need for technological improvements and suggest potential ways of advancing this area

How do neurons work together? Lessons from auditory cortex

Recordings of single neurons have yielded great insights into the way acoustic stimuli are represented in auditory cortex. However, any one neuron functions as part of a population whose combined activity underlies cortical information processing. Here we review some results obtained by recording simultaneously from auditory cortical populations and individual morphologically identified neurons, in urethane-anesthetized and unanesthetized passively listening rats. Auditory cortical populations produced structured activity patterns both in response to acoustic stimuli, and spontaneously without sensory input. Population spike time patterns were broadly conserved across multiple sensory stimuli and spontaneous events, exhibiting a generally conserved sequential organization lasting approximately 100 ms. Both spontaneous and evoked events exhibited sparse, spatially localized activity in layer 2/3 pyramidal cells, and densely distributed activity in larger layer 5 pyramidal cells and putative interneurons. Laminar propagation differed however, with spontaneous activity spreading upward from deep layers and slowly across columns, but sensory responses initiating in presumptive thalamorecipient layers, spreading rapidly across columns. In both unanesthetized and urethanized rats, global activity fluctuated between "desynchronized" state characterized by low amplitude, high-frequency local field potentials and a "synchronized" state of larger, lower-frequency waves. Computational studies suggested that responses could be predicted by a simple dynamical system model fitted to the spontaneous activity immediately preceding stimulus presentation. Fitting this model to the data yielded a nonlinear self-exciting system model in synchronized states and an approximately linear system in desynchronized states. We comment on the significance of these results for auditory cortical processing of acoustic and non-acoustic information