Parallel Processing Pathways in the Subcortical System Tonotopic/core: ICC MGv A1 (core) Non-tonotopic/diffuse: ICX MGm/MGd Belt/parabelt).
Auditory Cortex is Comprised of Multiple Fields Cat Human Bat Macaque Human
Topographic Organization Primary auditory cortical areas (core areas) respond best to tones, and are tonotopically organized. Borders between fields marked by reversal in tonotopic gradient. Belt fields less responsive to tones, respond best to NB noise, yet share tonotopy of adjacent core fields. Adjacent fields interconnect more extensively than non- adjacent fields. Macaque Hackett, Stepniewska, Kaas (1998) JCN 394: 475-495
Functional Organization of Isofrequency Slabs in A1: Evidence from Anaesthetized Cat As in the ICC, receptive field properties are systematically organized in hypercolumns within iso-CF slabs: Spectral selectivity (integration; i.e., tuning curve width, Q) Threshold Latency FM sweep direction, sweep rate selectivity Binaural Interaction
Functional Organization of Isofrequency Slabs in A1: Evidence from Anaesthetized Cat Spectral selectivity or integration (tuning width, Q) NB = Narrow band BB = Broad band Q 40dB Frequency High (rostral) Read et al. (2002) Low (caudal)
Functional Organization of Isofrequency Slabs in Cat A1 … FM sweep direction preference and rate selectivity Up Down Fast Slow Up Fast Mendelson et al. (1993)
Functional Organization of Isofrequency Slabs in Cat A1 …Binaural Interactions: Represented in elongated bands in cat AC Bands with similar binaural properties are interconnected across fields ipsilaterally, and contralaterally. EE: Binaural Summation (ITD) EI: Binaural Suppression (IID)
Space Map in Auditory Cortex? Spatial selectivity is relatively poor. No evidence for systematic map of space. Alternate theory: Location encoded by populations of neurons with modest spatial selectivity.
Functional Organization of Primate A1 In awake behaving monkeys, evidence for internal organization is not as strong as that in anaesthetized cats (methodological?). Primate rostral field neurons have longest latencies, and narrowest frequency and intensity tuning A1 has shortest latencies, moderate tuning. Caudomedial field has broadest frequency tuning Lateral field neurons have monotonic R/L functions.
Spectral Domain Properties Classically-defined receptive fields resemble those at thalamic and IC levels. More multi-peaked response areas are found. Recanzone et al. (2000)
Spectrotemporal Response Areas Response areas are the result of interactions between excitation and inhibition. However, the time course of excitation and inhibition may vary. STRAs try to capture the time-dependency of E – I interactions to reveal dynamic spectral filtering. Classical Frequency Response Area
Spectrotemporal Response Areas Reverse correlation technique: Find which stimulus feature correlated most strongly with the response. STRAs can be used to design optimal stimuli. DeCharms et al. (1998)
Spectrotemporal Response Areas Edge detection (I.e., response to low pass or high pass noise). Orientation and direction specificity: response to FM sweeps with particular modulation direction and speed. Optimal stimuli generate much higher response rates than tonal stimuli.
Spectrotemporal Response Areas Edge detection (i.e., response to low pass or high pass noise). Orientation and direction specificity: response to FM sweeps with particular modulation direction and speed. Optimal stimuli generate much higher response rates than tonal stimuli.
Spectro-temporal Facilitation (Combination Sensitivity) Combination sensitivity may underlie rapid discrimination of vowels. Kent & Read (1991)
Combination Sensitivity in Primates 66% of macaque A1 neurons are enhanced by presentation of tone combinations of different frequencies. Brosch et al. (1999)
Responses to Complex Sounds and Vocalizations Many neurons show specificity for sets of complex sounds, e.g., certain vocalizations, even specific combinations of utterances. But theres little evidence for specificity to a unique sound (e.g., Grandmas name cell). Klug et al. (2002)
Processing Signals in Noise In auditory nerve fibers, background noise raises tonal thresholds, shifts rate level functions to the right, compresses dynamic range. In A1, same stimuli generate increase in threshold, shift to right, but without compression.
Outputs of AC A1 projects subcortically to ICdc, MGB, pontine gray. AC belt and parabelt regions project to Superior temporal gyrus and sulcus Ventral prefrontal (cognition; saccade initiation) insular (multimodal: limbic, hippocampus) Caudal AC belt regions project to LIP, lateral interparietal area (spatial; projects to dorsal premotor cortex.
Projections to Prefrontal Cortex Belt and Parabelt AC project to rostral STS/STG. …and ventral prefrontal cortex. Auditory responses prevalent in ventrolateral PFC (areas 12, 45): corresponds to Brocas area in humans. Rostro-caudal gradient of projections Romanski et al. (1999)
Cortical Plasticity Functional organization is maintained by experience. E.g., Representation of frequency is massively altered by pairing stimulation with cholinergic nucleus basalis of the forebrain. 9 kHz (± 1/3 octave) Kilgard and Merzenich (1998) Before After 250 ms tones paired with nucleus basalis stimulation.
Cortical Plasticity Experience-dependent plasticity develops over time… …and dramatically increases with temporal complexity. Conclusion: auditory cortical organization is strongly influenced by behavioral significance of acoustic stimulus. Train of 15 ms tones paired with nucleus basalis stimulation. Kilgard and Merzenich (1998) Control