Odor identification errors reveal cognitive aspects of age-associated smell loss.

Human olfaction can be extraordinarily sensitive, and its most common assessment method is odor identification (OID), where everyday odors are matched to word labels in a multiple-choice format. However, many older persons are unable to identify familiar odors, a deficit that is associated with the risk of future dementia and mortality. The underlying processes subserving OID in older adults are poorly understood. Here, we analyzed error patterns in OID to test whether errors could be explained by perceptual and/or semantic similarities among the response alternatives. We investigated the OID response patterns in a large, population-based sample of older adults in Sweden (n = 2479; age 60-100 years). Olfaction was assessed by a 'Sniffin ́ TOM OID test with 16 odors; each trial involved matching a target odor to a correct label among three distractors. We analyzed the pattern of misidentifications, and the results showed that some distractors were more frequently selected than others, suggesting cognitive or perceptual factors may be present. Relatedly, we conducted a large online survey of older adults (n = 959, age 60-90 years) who were asked to imagine and rate the perceptual similarity of the target odors and the three corresponding distractors (e.g. "How similar are these smells: apple and mint?"). We then used data from the Swedish web corpus and the Word2Vec neural network algorithm to quantify the semantic association strength between the labels of each target odor and its three distractors. These data sources were used to predict odor identification errors. We found that the error patterns were partly explained by both the semantic similarity between target-distractor pairs, and the imagined perceptual similarity of the target-distractor pair. Both factors had, however, a diminished prediction in older ages, as responses became gradually less systematic. In sum, our results suggest that OID tests not only reflect olfactory perception, but also likely involve the mental processing of odor-semantic associations. This may be the reason why these tests are useful in predicting dementia onset. Our insights into olfactory-language interactions could be harnessed to develop new olfactory tests that are tailored for specific clinical purposes.

Perceptual odor qualities predict successful odor identification in old age.

Odor identification is a common assessment of olfaction, and it is affected in a large number of diseases. Identification abilities decline with age, but little is known about whether there are perceptual odor features that can be used to predict identification. Here, we analyzed data from a large, population-based sample of 2,479 adults, aged 60 years or above, from the Swedish National study on Aging and Care in Kungsholmen. Participants performed both free and cued odor identification tests. In a separate experiment, we assessed perceived pleasantness, familiarity, intensity, and edibility of all odors in the first sample, and examined how odor identification performance is associated with these variables. The analysis showed that high-intensity odors are easier to identify than low-intensity odors overall, but also that they are more susceptible to the negative repercussions of old age. This result indicates that sensory decline is a major aspect of age-dependent odor identification impairment, and suggests a framework where identification likelihood is proportional to the perceived intensity of the odor. Additional analyses further showed that high-performing individuals can discriminate target odors from distractors along the pleasantness and edibility dimensions and that unpleasant and inedible odors show smaller age-related differences in identification. Altogether, these results may guide further development and optimization of brief and efficient odor identification tests as well as influence the design of odorous products targeted toward older consumers.

Predicting complex spikes in striatal projection neurons of the direct pathway following neuromodulation by acetylcholine and dopamine.

The input structure of the basal ganglia, striatum, receives dense neuromodulatory input in the form of dopamine and acetylcholine. The two systems are tightly connected, for example, synchronized activity of cholinergic interneurons, leading to increased acetylcholine release, has been shown to directly trigger dopamine release from dopaminergic terminals in striatum. Both signals are further needed for induction of locomotion. High dopamine concentration leads to increased excitability of the direct pathway striatal projection neurons. High cholinergic tone inhibits various potassium channels further increasing the excitability of striatal projection neurons. Here, we investigate the combined effect of concurrent high acetylcholine and dopamine using biophysically detailed models based on rodent data. The aim of the study is to investigate how neuromodulation affects dendritic integration. The result shows that neuromodulation paired with synaptic activation of dendrites can give rise to complex spiking patterns, resembling spike shapes seen in the hippocampus. In the hippocampus, these complex spikes are associated with behavioral time scale plasticity and place cell tuning. We further investigate the mechanisms behind the complex spikes and find that there are two components, one axo-somatic and one dendritic in origin.

The microcircuits of striatum in silico.

The basal ganglia play an important role in decision making and selection of action primarily based on input from cortex, thalamus, and the dopamine system. Their main input structure, striatum, is central to this process. It consists of two types of projection neurons, together representing 95% of the neurons, and 5% of interneurons, among which are the cholinergic, fast-spiking, and low threshold-spiking subtypes. The membrane properties, soma-dendritic shape, and intrastriatal and extrastriatal synaptic interactions of these neurons are quite well described in the mouse, and therefore they can be simulated in sufficient detail to capture their intrinsic properties, as well as the connectivity. We focus on simulation at the striatal cellular/microcircuit level, in which the molecular/subcellular and systems levels meet. We present a nearly full-scale model of the mouse striatum using available data on synaptic connectivity, cellular morphology, and electrophysiological properties to create a microcircuit mimicking the real network. A striatal volume is populated with reconstructed neuronal morphologies with appropriate cell densities, and then we connect neurons together based on appositions between neurites as possible synapses and constrain them further with available connectivity data. Moreover, we simulate a subset of the striatum involving 10,000 neurons, with input from cortex, thalamus, and the dopamine system, as a proof of principle. Simulation at this biological scale should serve as an invaluable tool to understand the mode of operation of this complex structure. This platform will be updated with new data and expanded to simulate the entire striatum.

Basal Ganglia Neuromodulation Over Multiple Temporal and Structural Scales-Simulations of Direct Pathway MSNs Investigate the Fast Onset of Dopaminergic Effects and Predict the Role of Kv4.2.

The basal ganglia are involved in the motivational and habitual control of motor and cognitive behaviors. Striatum, the largest basal ganglia input stage, integrates cortical and thalamic inputs in functionally segregated cortico-basal ganglia-thalamic loops, and in addition the basal ganglia output nuclei control targets in the brainstem. Striatal function depends on the balance between the direct pathway medium spiny neurons (D1-MSNs) that express D1 dopamine receptors and the indirect pathway MSNs that express D2 dopamine receptors. The striatal microstructure is also divided into striosomes and matrix compartments, based on the differential expression of several proteins. Dopaminergic afferents from the midbrain and local cholinergic interneurons play crucial roles for basal ganglia function, and striatal signaling via the striosomes in turn regulates the midbrain dopaminergic system directly and via the lateral habenula. Consequently, abnormal functions of the basal ganglia neuromodulatory system underlie many neurological and psychiatric disorders. Neuromodulation acts on multiple structural levels, ranging from the subcellular level to behavior, both in health and disease. For example, neuromodulation affects membrane excitability and controls synaptic plasticity and thus learning in the basal ganglia. However, it is not clear on what time scales these different effects are implemented. Phosphorylation of ion channels and the resulting membrane effects are typically studied over minutes while it has been shown that neuromodulation can affect behavior within a few hundred milliseconds. So how do these seemingly contradictory effects fit together? Here we first briefly review neuromodulation of the basal ganglia, with a focus on dopamine. We furthermore use biophysically detailed multi-compartmental models to integrate experimental data regarding dopaminergic effects on individual membrane conductances with the aim to explain the resulting cellular level dopaminergic effects. In particular we predict dopaminergic effects on Kv4.2 in D1-MSNs. Finally, we also explore dynamical aspects of the onset of neuromodulation effects in multi-scale computational models combining biochemical signaling cascades and multi-compartmental neuron models.

Cell-type-specific inhibition of the dendritic plateau potential in striatal spiny projection neurons.

Striatal spiny projection neurons (SPNs) receive convergent excitatory synaptic inputs from the cortex and thalamus. Activation of spatially clustered and temporally synchronized excitatory inputs at the distal dendrites could trigger plateau potentials in SPNs. Such supralinear synaptic integration is crucial for dendritic computation. However, how plateau potentials interact with subsequent excitatory and inhibitory synaptic inputs remains unknown. By combining computational simulation, two-photon imaging, optogenetics, and dual-color uncaging of glutamate and GABA, we demonstrate that plateau potentials can broaden the spatiotemporal window for integrating excitatory inputs and promote spiking. The temporal window of spiking can be delicately controlled by GABAergic inhibition in a cell-type-specific manner. This subtle inhibitory control of plateau potential depends on the location and kinetics of the GABAergic inputs and is achieved by the balance between relief and reestablishment of NMDA receptor Mg2+ block. These findings represent a mechanism for controlling spatiotemporal synaptic integration in SPNs.