Neural coding of temporal information and its topography in the auditory cortex.

A signifi cant challenge for auditory neuroscience lies in the quest for a thorough understanding of how highly complex stimuli, such as human speech and other animal vocal signals, are encoded. Speech has components that vary on a timescale from the relatively slow (< 40 Hz), as with the rhythm of phonemes, to more rapid features (>100 Hz) that potentially provide the cues needed to identify a speaker’s voice (Rosen 1992). The auditory cortex is involved in the processing of these complex sounds (Heffner and Heffner 1984; Fitch et al. 1997; Mesgarani et al. 2008; Woolley et al. 2009) and most cortical neuron responses are timing-locked to the lower range of modulation (Joris et al. 2004). Much work still needs to be done to elucidate what specifi c combination of neural response characteristics, connectivity and network organization are needed to permit the exquisite feature selectivity needed for speech recognition. Two of the response characteristics of cortical neurons that have been attributed to the coding for temporal stimulus features include precise spike timing in the coding of slow repetition sounds and fi ring rate for faster repetition sounds (Joris et al. 2004; Schulze and Langner 1997; Lu et al. 2001). Interspike intervals also potentially serve as a code for temporal processing, but have not been investigated as extensively as spike timing and fi ring rate (Cariani 1999). A recent study published in PLoS One, by Imaizumi and colleagues (2010), helps to elucidate the important components of temporal processing and its cortical representation, by extensively surveying the topographic organization and information content of different aspects of such temporal processing. The authors used slow repetition rate click trains (1–30 Hz) to investigate spike-timing precision, fi ring rate and inter-stimulus intervals, and obtained repetition rate transfer functions in order to quantify responses. They found that all three of these measures provide information on slow repetition rate stimuli, but the amount of inter-stimulus interval information is signifi cantly greater than that of either of the other measures alone. They point out that, in fact, spike-timing precision and fi ring-rate parameters each contribute to the information content of inter-stimulus interval, and that there is additional evidence of some non-redundancy in the different representations, so that concurrent employment of these different codes potentially provides complementary information about stimuli. This may be advantageous for signal processing in natural settings where less than ideal circumstances are the norm, such as low signalto- noise ratios and the presence of multiple sound sources. In addition to the response characteristics of individual cortical neurons, analyses of neurophysiological data have revealed spectral response features that can be mapped topographically: e.g. tonotopic maps found across taxa (Reale and Imig 1980; Müller and Leppelsack 1985; Thomas et al. 2006). In contrast to the spectral features, the representation of temporal information does not show a straightforward topographic mapping in the auditory cortex. In the paper by Imaizumi and colleagues, the spatial organization of the different response categories discussed above was also mapped in the cortex, as well as additional categories such as characteristic frequency and Q40 (a spectral bandwidth measure). They produced Voronoi–Dirichlet tessellation maps corresponding to the anterior audio fi eld for each response category, and quantitatively analysed the spatial distribution patterns for the different temporal and spectral measures. The analyses of all cortical maps showed a general feature of local clustering for similar functional properties. Responses to the click train stimulation revealed this clustering to be non-homogenous for each of the temporal response measures. In general, cortical organization in regards to these parameters was less globally organized than what is observed for spectral measures. The differing spatial organization for each of the three stimulus repetition codes (spike-timing precision, fi ring rate and inter-stimulus interval) suggest that they operate somewhat separately, and the authors interpret the locally differing spatial patterns as evidence that helps to clarify multiple, concurrent processing streams. Together, the data collected by Imaizumi and colleagues suggest that cortical neurons employ multiple strategies in the processing of sounds that are characterized by low repetition rates. Their paper helps to clarify the roles played by timing and place coding in the analysis of repeating stimuli. Understanding these roles is essential for increasing our knowledge of how complex stimuli such as speech are encoded. Further work along these lines, including single unit recordings and recordings from awake preparations, should provide even greater insights into the encoding of speech and other sounds.

Single-neuron encoding of surprise in auditory processing.

The main role of structures in ascending sensory systems is to extract raw features of sensory input and compartmentalize the information-bearing elements for use by the brain. Information-bearing elements can be apparent, as in the case of stimulus frequency or intensity (Ehret and Merzenich 1988; Tramo et al. 2002; Yu et al. 2010). The features of sound that drive neuronal fi ring at higher auditory centers, however, remain elusive. In their exciting article, Gill and colleagues (2008) show how “surprise” is a dimension of auditory experience that alters fi ring patterns of central auditory neurons. By elaborating the method for calculating and extracting spectro-temporal receptive fi elds (STRFs), the authors demonstrate that auditory neurons, mainly those from hierarchically higher-order areas, modulate their discharge rates in response to sound elements that deviate from expected values. This work is the fi rst to capture and separate encoding due to surprise from the ongoing encoding of spectral and temporal elements of acoustic cues (Theunissen et al. 2004). The coding of auditory information was studied in a highly social songbird species, the zebra fi nch (Taeniopygia guttata), which frequently engages in vocal exchange as part of its normal behaviour (for reviews, see Zeigler and Marler 2004). On the receiving (sensory) end of this exchange, the acoustic elements of the incoming birdsong, including notes and syllables, are encoded by auditory neurons (for reviews, see Mello et al. 2004; Gentner 2004). As with words in human speech, for a song to be recognizable over repeated use, the order of all of its individual sound elements must also be largely preserved across time. Consequently, songbirds naturally generate expectations not only for specifi c songs but also for the general structural rules, internal correlations or probability statistics that apply to song elements. To determine if surprise was predictive of altered neuronal activity, electrophysiological recordings were made in key structures of the ascending auditory pathway, including the songbird analogue of the mammalian inferior colliculus (nucleus MLd), the primary auditory forebrain area (Field L2) or an association auditory forebrain area (CLM) (Vates et al. 1996; Mello et al. 1998). One of the main goals of this work was to isolate the impact of surprise on auditory encoding for different cells (Gill et al. 2008). To this end, different forms of STRF were compared, including a STRF that was specifi cally developed to capture the impact of fi ring due to unmet expectations in stimulus structure (a surprise-STRF). In order to drive neuronal fi ring by surprise, Gill and colleagues generated song stimuli in which certain song elements were louder or softer than expected. Deviations were only introduced as changes in power for a particular element given a brief sample of “stimulus history”. This manipulation allowed for the measured and elegant application of “surprise” embedded on the song elements without having to interpret surprise in the context of the entire song. The authors show that surprise-STRF had far greater predictive strength relative to other STRF metrics and, therefore, was useful to parse out and quantify changes in fi ring given the probability of that change occurring based on prior experience. Surprise-STRFs were shown to have provided improvement in predictive power for select neurons at all three levels of the auditory pathway that were tested. Great gains in prediction were, however, frequently made by surprise-STRFs in the higher-order auditory area CLM, for two dominant cell types named by the authors as off-set and complex auditory neurons. Interestingly, in neurons that are surprise-responsive, Gill and colleagues found that the degree of altered fi ring was relatable, in linear terms, to the magnitude of change introduced. In addition, surprise coding was directionally sensitive; surprises to augmented stimulus power could be encoded at an entirely different sub-set of neurons than cells tuned to the surprise of a lower than expected stimulus power.

mGluR5 is a central regulator of synaptic function and plasticity in the developing mouse barrel cortex.

Glutamate, the main excitatory neurotransmitter in the vertebrate brain, acts both on ligand-gated ion channels as well as on metabotropic receptors (mGluRs), which engage an array of biochemical regulatory pathways via activation of G-proteins. mGluRs have been shown to exert central roles in the regulation of neuronal excitability by both pre- and post-synaptic mechanisms, and consequently have been implicated in a variety of central nervous system functions that include, but are not limited to, learning, pain perception and anxiety. There exists three groups of mGluRs (types I, II and III), accounting for a total of eight different mGluR types (mGluR1-8) (Hollmann and Heinemann 1994). Group I mGluRs, which encompass mGluR1 and mGluR5, engage Gq-dependent second messenger systems which, in turn, regulate post-synaptic activity and local protein synthesis. Abnormal signalling through group I mGluRs have been associated with a series of neurological disorders including Fragile X syndrome and schizophrenia (Dolen and Bear 2008; Krivoy et al. 2008). Importantly, group I mGluRs have been shown to regulate synaptic plasticity both in developing and adult organisms. Noteworthy, genetic or pharmacological manipulations directed at mGluR5-containing receptors signifi cantly impair learning and memory formation (Lu et al. 1997; Chiamulera et al. 2001). These roles for mGluR5 correlate with marked experience-dependent changes in synaptic strength, including long-term potentiation and depression (Eckert and Racine 2004). The impact of mGluR5 activity on synaptic function and plasticity suggested that activation of this receptor may constitute a central molecular component underlying the developmental establishment and/or experience-dependent refi nement of sensory maps found in primary sensory cortex of mammals. Such a role for mGluR5 was recently confi rmed in an elegant study by She and colleagues (2009) recently published in the European Journal of Neuroscience. These authors report that mice devoid of the mGluR5 receptor expression (mGluR5–/–) lack the normal arrangement of thalamocortical afferents and layer IV cell bodies associated with the rostral smaller whiskers of the facial vibrissal system, commonly referred to as the barrel cortex. Interestingly, the anatomical organisation of the thalamocortical afferents carrying information from the caudal and larger vibrissae was preserved in mGluR5–/– mice. These animals, however, lack the aggregation of the cortical layer IV cell bodies into clusters that would, in wild-type or heterozygous mice (mGluR5+/–), exclusively represent each vibrissa. In addition, it was found that mGluR5-null mice exhibit a striking mis-alignment of the dendritic fi elds of spiny stellate neurons, which contribute to the formation of the classic columnar neuronal arrangements typical of the barrel cortex. In particular, in intact mice, dendritic fi elds of layer IV neurons are normally oriented towards the barrel center, an organisation that putatively oversamples inputs from the dominant vibrissae to sharpen the perceptual experience of sensory drive from each whisker (Harris and Woolsey 1981). In mGluR5-defi cient mice, dendritic fi elds are more dispersed suggesting that pruning or mobility may be mal-adaptive in these animals, and may ultimately compromise the resolution at which sensory input can be processed. It was found that at post-natal weeks 2–3, mGluR5–/– mice failed to show the expected polarisation of dendritic fi elds towards the barrel center and that this abnormal pattern persists into adulthood. Interestingly, the anatomical patterning of axonal terminations from thalamocortical afferents was appropriate for barrel formation, and functional synaptic transmission for sensory-driven responses was spared. Malformation of the barrel cortex in mGluR5–/– therefore appears to result from abnormalities in intra-cortical properties and localised to post-synaptic neurons targeted by the thalamocortical afferents. Consistent with abnormalities in the formation of the barrel cortex in mGluR5–/– mice, these mutant animals show reduced latency to the surround whisker responses. This feature is shared with barrelless.

A songbird forebrain area potentially involved in auditory discrimination and memory formation.

Songbirds rely on auditory processing of natural communication signals for a number of social behaviors,including mate selection,individual recognition and the rare behavior of vocal learning - the ability to learn vocalizations through imitation of an adult model,rather than by instinct.Like mammals,songbirds possess a set of interconnected ascending and descending auditory brain pathways that process acoustic information and that are presumably involved in the perceptual processing of vocal communication signals.Most auditory areas studied to date are located in the caudomedial forebrain of the songbird and include the thalamo-recipient field L (sub fields L1,L2 and L3),the caudomedial and caudolateral mesopallium (CMM and CLM,respectively) and the caudomedial nidopallium (NCM). This review focuses on NCM,an auditory area previously proposed to be analogous to parts of the primary auditory cortex in mammals.Stimulation of songbirds with auditory stimuli drives vigorous electrophysiological responses and the expression of several activity-regulated genes in NCM.Interestingly,NCM neurons are tuned to species-specific songs and undergo some forms of experience-dependent plasticity in-vivo .These activity-dependent changes may underlie long-term modifications in the functional performance of NCM and constitute a potential neural substrate for auditory discrimination.We end this review by discussing evidence that suggests that NCM may be a site of auditory memory formation and/or storage.