Representations of specific acoustic patterns in the auditory cortex and hippocampus

Previous behavioural studies have shown that repeated presentation of a randomly chosen acoustic pattern leads to the unsupervised learning of some of its specific acoustic features. The objective of our study was to determine the neural substrate for the representation of freshly learnt acoustic patterns. Subjects first performed a behavioural task that resulted in the incidental learning of three different noise-like acoustic patterns. During subsequent high-resolution functional magnetic resonance imaging scanning, subjects were then exposed again to these three learnt patterns and to others that had not been learned. Multi-voxel pattern analysis was used to test if the learnt acoustic patterns could be 'decoded' from the patterns of activity in the auditory cortex and medial temporal lobe. We found that activity in planum temporale and the hippocampus reliably distinguished between the learnt acoustic patterns. Our results demonstrate that these structures are involved in the neural representation of specific acoustic patterns after they have been learnt

Auditory training changes temporal lobe connectivity in Wernicke's aphasia: a randomised trial

Introduction Aphasia is one of the most disabling sequelae after stroke, occurring in 25%–40% of stroke survivors. However, there remains a lack of good evidence for the efficacy or mechanisms of speech comprehension rehabilitation. Trial Design This within-subjects trial tested two concurrent interventions in 20 patients with chronic aphasia with speech comprehension impairment following left hemisphere stroke: (1) phonological training using ‘Earobics’ software and (2) a pharmacological intervention using donepezil, an acetylcholinesterase inhibitor. Donepezil was tested in a double-blind, placebo-controlled, cross-over design using block randomisation with bias minimisation. Methods The primary outcome measure was speech comprehension score on the comprehensive aphasia test. Magnetoencephalography (MEG) with an established index of auditory perception, the mismatch negativity response, tested whether the therapies altered effective connectivity at the lower (primary) or higher (secondary) level of the auditory network. Results Phonological training improved speech comprehension abilities and was particularly effective for patients with severe deficits. No major adverse effects of donepezil were observed, but it had an unpredicted negative effect on speech comprehension. The MEG analysis demonstrated that phonological training increased synaptic gain in the left superior temporal gyrus (STG). Patients with more severe speech comprehension impairments also showed strengthening of bidirectional connections between the left and right STG. Conclusions Phonological training resulted in a small but significant improvement in speech comprehension, whereas donepezil had a negative effect. The connectivity results indicated that training reshaped higher order phonological representations in the left STG and (in more severe patients) induced stronger interhemispheric transfer of information between higher levels of auditory cortex

Working memory for time intervals in auditory rhythmic sequences

The brain can hold information about multiple objects in working memory. It is not known, however, whether intervals of time can be stored in memory as distinct items. Here, we developed a novel paradigm to examine temporal memory where listeners were required to reproduce the duration of a single probed interval from a sequence of intervals. We demonstrate that memory performance significantly varies as a function of temporal structure (better memory in regular vs. irregular sequences), interval size (better memory for sub- vs. supra-second intervals), and memory load (poor memory for higher load). In contrast memory performance is invariant to attentional cueing. Our data represent the first systematic investigation of temporal memory in sequences that goes beyond previous work based on single intervals. The results support the emerging hypothesis that time intervals are allocated a working memory resource that varies with the amount of other temporal information in a sequence

Brain Bases of Working Memory for Time Intervals in Rhythmic Sequences

Perception of auditory time intervals is critical for accurate comprehension of natural sounds like speech and music. However, the neural substrates and mechanisms underlying the representation of time intervals in working memory are poorly understood. In this study, we investigate the brain bases of working memory for time intervals in rhythmic sequences using functional magnetic resonance imaging. We used a novel behavioral paradigm to investigate time-interval representation in working memory as a function of the temporal jitter and memory load of the sequences containing those time intervals. Human participants were presented with a sequence of intervals and required to reproduce the duration of a particular probed interval. We found that perceptual timing areas including the cerebellum and the striatum were more or less active as a function of increasing and decreasing jitter of the intervals held in working memory respectively whilst the activity of the inferior parietal cortex is modulated as a function of memory load. Additionally, we also analyzed structural correlations between gray and white matter density and behavior and found significant correlations in the cerebellum and the striatum, mirroring the functional results. Our data demonstrate neural substrates of working memory for time intervals and suggest that the cerebellum and the striatum represent core areas for representing temporal information in working memory

Neural Basis of Working Memory for Time Intervals

AbstractThe brain can hold information about multiple environmental objects in working memory. It is not known, however, whether time intervals can be treated similarly as “sensory objects” and stored in memory as distinct items. Here, we designed a new paradigm to measure the precision of memory for time intervals. Listeners were required to remember and match the duration of a probed interval from a sequence of intervals and the precision of the response was evaluated as an index of memory (Bays & Husain, 2008). Behavioural data indicated that memory for a single sub-second time interval was significantly modulated by temporal regularity and the number of intervals in the sequence (Teki & Griffiths, 2013).In this functional magnetic resonance imaging study, we specifically aimed to examine the brain areas that encode memory for time as a function of rhythmic context and memory load. Based on previous work, we hypothesized a role for both striatum and cerebellum in encoding time in a beat-based and duration-based manner respectively (Teki et al., 2011, 2012) and a role for the parietal and prefrontal cortex in encoding the memory load. Four different levels of temporal regularity (5-10%, 20-25%, 35- 40%, and 50-55% jitter) and working memory load (1-4 intervals) were used in an orthogonal design where jitter was varied across sequences with fixed number of intervals (4) and number of intervals were varied across sequences with a fixed jitter (20- 25%). Functional imaging data were acquired using a sparse sampling protocol in a 3T Siemens Trio scanner whilst participants were performing the task.Parametric analysis of data from 12 participants so far revealed activation in both striatum and cerebellum, with stronger striatal and cerebellar activity as a function of decreasing and increasing jitter respectively. Analysis of brain areas that parametrically encode increasing number of time intervals revealed significant clusters in the parietal cortex and cerebellum. Our data go beyond previous work examining memory during single interval discrimination tasks and reveal context-dependent correlates of memory for time intervals (Merchant et al., 2013) that vary as a function of the rhythmic context and the working memory load of the sequences. The data suggests a critical role for subcortical timing networks in the basal ganglia and the cerebellum in mediating rhythmic timing and the parietal cortex in representing the memory load